{"id":3564,"date":"2026-09-16T13:40:32","date_gmt":"2026-09-16T06:40:32","guid":{"rendered":"https:\/\/dgway.com\/blog_E\/?p=3564"},"modified":"2026-09-16T18:08:31","modified_gmt":"2026-09-16T11:08:31","slug":"from-gpu-to-edge-fpga-balancing-image-quality-and-resources-for-super-resolution-on-amd-kria-kv260","status":"publish","type":"post","link":"https:\/\/dgway.com\/blog_E\/2026\/09\/16\/from-gpu-to-edge-fpga-balancing-image-quality-and-resources-for-super-resolution-on-amd-kria-kv260\/","title":{"rendered":"From GPU to Edge FPGA: Balancing Image Quality and Resources for Super-Resolution on AMD Kria\u2122 KV260"},"content":{"rendered":"\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"211\" src=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/08\/Alinx-AX7010-1024x211.png\" alt=\"\" class=\"wp-image-3390\" srcset=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/08\/Alinx-AX7010-1024x211.png 1024w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/08\/Alinx-AX7010-300x62.png 300w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/08\/Alinx-AX7010-767x158.png 767w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/08\/Alinx-AX7010-1536x316.png 1536w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/08\/Alinx-AX7010-2048x422.png 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n\n\n\n<style>\n  \/* =========================================\n     1. 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Media Queries\n     ========================================= *\/\n  @media (max-width: 768px) {\n    .dg-vs-grid { grid-template-columns: 1fr; }\n    .dg-quote-text { font-size: 2.1rem; text-align: left; }\n    .dg-to-value { font-size: 3rem; }\n    .dg-to-op-box { left: 10%; right: 10%; }\n    .dg-spectrum-line { display: none; }\n    .dg-spectrum-nodes {\n      flex-direction: column;\n      align-items: center;\n      gap: 40px;\n    }\n    .dg-spec-node { max-width: 100%; }\n    .dg-spec-node.highlight .dg-spec-icon { margin-top: 0; }\n  }\n<\/style>\n\n\n\n<div class=\"dg-blog-wrapper\">\n  <p><strong>A super-resolution model can look excellent on a GPU. The real challenge starts when the same capability must operate inside a UAV, remote-sensing payload, or compact edge system.<\/strong><\/p>\n\n  <p>In these applications, high-resolution imagery is valuable, but the hardware budget is limited. Memory, power consumption, heat, processing latency, and board size all become part of the AI design. The best algorithm is therefore not always the model with the highest image-quality score. The practical target is the model that delivers <strong>enough image quality within the available edge resources<\/strong>.<\/p><\/div>\n\n\n\n<div class=\"wp-block-group is-layout-grid wp-container-core-group-is-layout-1e2e5166 wp-block-group-is-layout-grid\">\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"576\" src=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/09\/cover-1-1024x576.jpg\" alt=\"\" class=\"wp-image-3670\" srcset=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/09\/cover-1-1024x576.jpg 1024w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/09\/cover-1-300x169.jpg 300w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/09\/cover-1-768x432.jpg 768w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/09\/cover-1-1536x864.jpg 1536w, https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/09\/cover-1-2048x1152.jpg 2048w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-boldblocks-icon-separator\" role=\"separator\"><div class=\"wp-block-boldblocks-icon-separator__inner icon-center is-align-center\" style=\"--bb-border:1px solid;--bb--icon-width:1em;--bb--icon-spacing:.5em\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" xml:space=\"preserve\" viewBox=\"0 0 20 20\">\n  <path d=\"M6.1 9.5V8.4c0-.5-.2-.7-.7-.8.6-.1.8-.3.8-.9V5.6c0-.4.1-.5.7-.5h.3v-.5h-.6c-.9 0-1.3.2-1.3 1 0 .5.1.8.1 1.2 0 .2-.2.5-.9.5v.6c.7 0 .9.3.9.5 0 .4-.1.7-.1 1.2 0 .8.4 1 1.3 1h.5V10h-.3c-.5 0-.7-.1-.7-.5m10.4 4.4c-.8-.8-1.7-1.4-2.6-2-.1-.1-1.1-1.1-1.5-1.4 2.4-4-1.1-9.2-5.7-8.5-4.4.7-6.3 6.2-3.2 9.4 1.7 1.9 4.6 2.3 6.9 1.1.6.6 1.1 1.1 1.6 1.7.7.9 1.2 1.8 2.1 2.5.6.5 1.4 1.2 2.3 1.3 1.1.1 1.7-.6 1.7-1.6-.1-.9-1-1.9-1.6-2.5m-8.9-2.3c-2.2 0-4-1.8-4-4s1.8-4 4-4 4 1.8 4 4-1.8 4-4 4m2.1-4.8c0-.4.1-.7.1-1.2 0-.8-.4-1-1.3-1H8v.5h.3c.5 0 .7.1.7.5v1.1c0 .5.2.7.7.8-.6.2-.8.4-.8.9v1.1c.1.4-.1.5-.6.5H8v.6h.5c.9 0 1.3-.2 1.3-1 0-.5-.1-.8-.1-1.2 0-.2.2-.5.9-.5v-.6c-.7 0-.9-.3-.9-.5\"><\/path>\n<\/svg><\/div><\/div>\n\n\n\n<div class=\"dg-blog-wrapper\">\n\n  <h2> The Edge-AI Problem: High Image Quality Under a Small Hardware Budget<\/h2>\n\n  <p class=\"dg-short-intro\">Remote-sensing systems must process imagery close to where it is captured. However, bringing AI to the edge means leaving power-hungry GPUs behind and working within strict hardware constraints.<\/p>\n\n  <!-- Graphics: Challenge vs Solution -->\n  <div class=\"dg-vs-grid\">\n    \n    <!-- Box 1: The Constraint -->\n    <div class=\"dg-vs-card challenge\">\n      <div class=\"dg-vs-header\">\n        <!-- Drone\/Camera Icon -->\n        <svg fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M12 19l9 2-9-18-9 18 9-2zm0 0v-8\"><\/path><\/svg>\n        <h4 class=\"dg-vs-title\">The Deployment Constraint<\/h4>\n      <\/div>\n      <ul class=\"dg-vs-list\">\n        <li>UAVs &amp; field cameras cannot carry GPU workstations.<\/li>\n        <li>Tighter power, thermal, and memory budgets.<\/li>\n        <li>Need for real-time edge processing.<\/li>\n      <\/ul>\n    <\/div>\n\n    <!-- Box 2: The AMD Solution -->\n    <div class=\"dg-vs-card solution\">\n      <div class=\"dg-vs-header\">\n        <!-- FPGA\/Chip Icon -->\n        <svg fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 3v2m6-2v2M9 19v2m6-2v2M5 9H3m2 6H3m18-6h-2m2 6h-2M7 19h10a2 2 0 002-2V7a2 2 0 00-2-2H7a2 2 0 00-2 2v10a2 2 0 002 2zM9 9h6v6H9V9z\"><\/path><\/svg>\n        <h4 class=\"dg-vs-title\">The AMD Kria\u2122 Solution<ls>   <\/ls><\/h4>\n      <\/div>\n      <ul class=\"dg-vs-list\">\n        <li>Combines processing resources &amp; programmable logic.<\/li>\n        <li>Compact platform with AI acceleration flow.<\/li>\n        <li><strong>Adapts the AI model<\/strong> to the equipment constraints.<\/li>\n      <\/ul>\n    <\/div>\n\n  <\/div>\n\n \n\n<\/div>\n\n\n\n<div class=\"wp-block-boldblocks-icon-separator\" role=\"separator\"><div class=\"wp-block-boldblocks-icon-separator__inner icon-center is-align-center\" style=\"--bb-border:1px solid;--bb--icon-width:1em;--bb--icon-spacing:.5em\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" xml:space=\"preserve\" viewBox=\"0 0 20 20\">\n  <path d=\"M6.1 9.5V8.4c0-.5-.2-.7-.7-.8.6-.1.8-.3.8-.9V5.6c0-.4.1-.5.7-.5h.3v-.5h-.6c-.9 0-1.3.2-1.3 1 0 .5.1.8.1 1.2 0 .2-.2.5-.9.5v.6c.7 0 .9.3.9.5 0 .4-.1.7-.1 1.2 0 .8.4 1 1.3 1h.5V10h-.3c-.5 0-.7-.1-.7-.5m10.4 4.4c-.8-.8-1.7-1.4-2.6-2-.1-.1-1.1-1.1-1.5-1.4 2.4-4-1.1-9.2-5.7-8.5-4.4.7-6.3 6.2-3.2 9.4 1.7 1.9 4.6 2.3 6.9 1.1.6.6 1.1 1.1 1.6 1.7.7.9 1.2 1.8 2.1 2.5.6.5 1.4 1.2 2.3 1.3 1.1.1 1.7-.6 1.7-1.6-.1-.9-1-1.9-1.6-2.5m-8.9-2.3c-2.2 0-4-1.8-4-4s1.8-4 4-4 4 1.8 4 4-1.8 4-4 4m2.1-4.8c0-.4.1-.7.1-1.2 0-.8-.4-1-1.3-1H8v.5h.3c.5 0 .7.1.7.5v1.1c0 .5.2.7.7.8-.6.2-.8.4-.8.9v1.1c.1.4-.1.5-.6.5H8v.6h.5c.9 0 1.3-.2 1.3-1 0-.5-.1-.8-.1-1.2 0-.2.2-.5.9-.5v-.6c-.7 0-.9-.3-.9-.5\"><\/path>\n<\/svg><\/div><\/div>\n\n\n\n<style>\n  \/* Minimal Blue Theme - Compact Timeline & Highlighted Logos (+0.8rem Font Scale) *\/\n  .dg-blog-wrapper {\n    font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Roboto, Oxygen-Sans, Ubuntu, Cantarell, \"Helvetica Neue\", sans-serif;\n    color: #334155;\n    line-height: 1.6;\n    font-size: 1.8rem !important; \/* Base 1.0 + 0.8 *\/\n  }\n\n  .dg-blog-wrapper h2 {\n    color: #0f172a;\n    font-size: 2.8rem !important; \/* Base 2.0 + 0.8 *\/\n    margin-top: 48px;\n    margin-bottom: 24px;\n    font-weight: 700;\n  }\n\n  .dg-intro-text {\n    margin-bottom: 40px;\n  }\n\n  \/* --- Space-Saving Horizontal Timeline --- *\/\n  .dg-timeline-container {\n    position: relative;\n    margin: 40px 0 60px 0;\n    padding: 20px 0;\n  }\n\n  \/* Connecting Background Line *\/\n  .dg-timeline-line {\n    position: absolute;\n    top: 44px; \/* Center of the dots *\/\n    left: 5%;\n    right: 5%;\n    height: 4px;\n    background: #e2e8f0;\n    z-index: 1;\n    border-radius: 2px;\n  }\n\n  \/* Flow Wrapper *\/\n  .dg-timeline-flow {\n    display: flex;\n    justify-content: space-between;\n    align-items: flex-start;\n    position: relative;\n    z-index: 2;\n  }\n\n  \/* Individual Step (No Box) *\/\n  .dg-time-step {\n    display: flex;\n    flex-direction: column;\n    align-items: center;\n    text-align: center;\n    flex: 1;\n    padding: 0 10px;\n  }\n\n  \/* The Dot\/Number *\/\n  .dg-time-dot {\n    width: 48px;\n    height: 48px;\n    background: #0284c7;\n    color: #ffffff;\n    border-radius: 50%;\n    display: flex;\n    align-items: center;\n    justify-content: center;\n    font-size: 1.8rem !important; \/* Base 1.0 + 0.8 *\/\n    font-weight: 800;\n    margin-bottom: 16px;\n    border: 4px solid #ffffff; \/* Creates a cutout effect over the line *\/\n    box-shadow: 0 4px 6px rgba(2, 132, 199, 0.2);\n    transition: transform 0.2s;\n  }\n\n  .dg-time-step:hover .dg-time-dot {\n    transform: scale(1.1);\n    background: #0369a1;\n  }\n\n  \/* Step Text *\/\n  .dg-time-text {\n    font-size: 1.6rem !important; \/* Base 0.8 + 0.8 *\/\n    font-weight: 600;\n    color: #0f172a;\n    line-height: 1.3;\n  }\n\n\n  \/* --- Prominent \"Powered By\" Banner --- *\/\n  .dg-powered-banner {\n    background: linear-gradient(135deg, #d6ebff, #98c6f5); \/* Dark premium background *\/\n    border-radius: 12px;\n    padding: 32px;\n    display: flex;\n    flex-direction: column;\n    align-items: center;\n    box-shadow: 0 10px 25px rgba(0, 0, 0, 0.1);\n    margin-bottom: 40px;\n  }\n\n  .dg-pb-title {\n    font-size: 2.4rem !important; \/* Base 0.7 + 0.8 *\/\n    color: #011b40;\n    text-transform: uppercase;\n    letter-spacing: 2px;\n    font-weight: 700;\n    margin-bottom: 24px;\n  }\n\n  .dg-pb-logos {\n    display: flex;\n    flex-wrap: wrap;\n    justify-content: center;\n    align-items: center;\n    gap: 40px;\n  }\n\n  .dg-pb-item {\n    display: flex;\n    align-items: center;\n    gap: 12px;\n    color: #000000;\n    font-size: 1.9rem !important; \/* Base 1.1 + 0.8 *\/\n    font-weight: 600;\n  }\n\n  \/* Standardizing Logo SVG sizes *\/\n  .dg-pb-item svg {\n    width: 36px;\n    height: 36px;\n  }\n\n  \/* Custom Styles for Specific Brand Logos *\/\n  .logo-pytorch { color: #ee4c2c; } \/* PyTorch Orange *\/\n  .logo-vitis { color: #38bdf8; }   \/* Vitis Blue *\/\n  .logo-amd-text { \n    font-family: Arial, Helvetica, sans-serif;\n    font-weight: 900;\n    letter-spacing: -1px;\n    font-size: 2.2rem !important; \/* Make AMD text robust *\/\n  }\n\n\n  \/* --- Mobile Responsiveness --- *\/\n  @media (max-width: 768px) {\n    \/* Convert horizontal timeline to a compact vertical one *\/\n    .dg-timeline-line {\n      top: 0;\n      bottom: 0;\n      left: 24px;\n      width: 4px;\n      height: auto;\n    }\n    .dg-timeline-flow {\n      flex-direction: column;\n      gap: 24px;\n    }\n    .dg-time-step {\n      flex-direction: row;\n      text-align: left;\n      padding: 0;\n      gap: 20px;\n    }\n    .dg-time-dot {\n      margin-bottom: 0;\n      z-index: 2; \/* Keep above line *\/\n    }\n    .dg-pb-logos {\n      gap: 24px;\n      flex-direction: column;\n    }\n  }\n<\/style>\n\n<div class=\"dg-blog-wrapper\">\n\n  <h2> From AERU-Net Research to a Complete Edge Deployment Flow<\/h2>\n\n  <!-- Intro Text -->\n  <div class=\"dg-intro-text\">\n    <p>Developed by MDAP (Chulalongkorn University), this workflow transitions the <strong>AERU-Net super-resolution architecture<\/strong> from GPU-based research to a real FPGA edge hardware deployment.<\/p>\n    <p>The system is optimized for quantization-friendly operation, supporting both <strong>\u00d72 and \u00d74 super-resolution<\/strong> for remote-sensing imagery.<\/p>\n  <\/div>\n\n  <!-- Minimal Horizontal Timeline (No Boxes) -->\n  <div class=\"dg-timeline-container\">\n    <div class=\"dg-timeline-line\"><\/div>\n    <div class=\"dg-timeline-flow\">\n      \n      <div class=\"dg-time-step\">\n        <div class=\"dg-time-dot\">1<\/div>\n        <div class=\"dg-time-text\">AERU-Net<br>Algorithm<\/div>\n      <\/div>\n      \n      <div class=\"dg-time-step\">\n        <div class=\"dg-time-dot\">2<\/div>\n        <div class=\"dg-time-text\">GPU Training<br>FP32 Baseline<\/div>\n      <\/div>\n      \n      <div class=\"dg-time-step\">\n        <div class=\"dg-time-dot\">3<\/div>\n        <div class=\"dg-time-text\">Model &amp; Operator<br>Optimization<\/div>\n      <\/div>\n      \n      <div class=\"dg-time-step\">\n        <div class=\"dg-time-dot\">4<\/div>\n        <div class=\"dg-time-text\">Quantization<br>Aware Training<\/div>\n      <\/div>\n      \n      <div class=\"dg-time-step\">\n        <div class=\"dg-time-dot\">5<\/div>\n        <div class=\"dg-time-text\">AMD Kria\u2122 KV260<br>Deployment<\/div>\n      <\/div>\n\n    <\/div>\n  <\/div>\n\n  <!-- Prominent \"Powered By\" Banner with Logos -->\n  <div class=\"dg-powered-banner\">\n    <div class=\"dg-pb-title\">Powered By<\/div>\n    <div class=\"dg-pb-logos\">\n      \n      <!-- PyTorch Logo (Flame representation) -->\n      <div class=\"dg-pb-item\">\n        <svg class=\"logo-pytorch\" viewBox=\"0 0 24 24\" fill=\"currentColor\">\n          <path d=\"M12 2C12 2 7 7.5 7 12C7 14.76 9.24 17 12 17C14.76 17 17 14.76 17 12C17 9.24 14.5 5.5 12 2ZM12 15C10.34 15 9 13.66 9 12C9 10.9 9.63 9.4 10.5 8.24C10.2 9.4 10.5 11 12 12C12 12 13.5 12.3 14 11.2C13.8 12.8 13.1 15 12 15Z\"><\/path>\n          <path d=\"M12 22C6.48 22 2 17.52 2 12C2 9.87 2.68 7.9 3.82 6.27L18.73 21.18C16.9 21.72 14.53 22 12 22ZM21.18 18.73L6.27 3.82C7.9 2.68 9.87 2 12 2C17.52 2 22 6.48 22 12C22 14.53 21.72 16.9 21.18 18.73Z\" opacity=\"0.3\"><\/path>\n        <\/svg>\n        <span>PyTorch<\/span>\n      <\/div>\n\n      <!-- Vitis AI Logo (AI\/Node representation) -->\n      <div class=\"dg-pb-item\">\n        <svg class=\"logo-vitis\" fill=\"none\" stroke=\"currentColor\" viewBox=\"0 0 24 24\" stroke-width=\"2\">\n          <path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M14 10l-2 1m0 0l-2-1m2 1v2.5M20 7l-2 1m2-1l-2-1m2 1v2.5M14 4l-2-1-2 1M4 7l2-1M4 7l2 1M4 7v2.5M12 21l-2-1m2 1l2-1m-2 1v-2.5M6 18l-2-1v-2.5M18 18l2-1v-2.5\"><\/path>\n          <circle cx=\"12\" cy=\"12\" r=\"3\" stroke=\"currentColor\" fill=\"#0f172a\"><\/circle>\n        <\/svg>\n        <span>Vitis AI<\/span>\n      <\/div>\n\n      <!-- AMD Kria Logo (Typography + Edge Icon) -->\n      <div class=\"dg-pb-item\">\n        <span class=\"logo-amd-text\">AMD<\/span>\n        <span>Kria\u2122 KV260<\/span>\n      <\/div>\n\n    <\/div>\n  <\/div>\n\n<\/div>\n\n\n\n<div class=\"wp-block-boldblocks-icon-separator\" role=\"separator\"><div class=\"wp-block-boldblocks-icon-separator__inner icon-center is-align-center\" style=\"--bb-border:1px solid;--bb--icon-width:1em;--bb--icon-spacing:.5em\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" xml:space=\"preserve\" viewBox=\"0 0 20 20\">\n  <path d=\"M6.1 9.5V8.4c0-.5-.2-.7-.7-.8.6-.1.8-.3.8-.9V5.6c0-.4.1-.5.7-.5h.3v-.5h-.6c-.9 0-1.3.2-1.3 1 0 .5.1.8.1 1.2 0 .2-.2.5-.9.5v.6c.7 0 .9.3.9.5 0 .4-.1.7-.1 1.2 0 .8.4 1 1.3 1h.5V10h-.3c-.5 0-.7-.1-.7-.5m10.4 4.4c-.8-.8-1.7-1.4-2.6-2-.1-.1-1.1-1.1-1.5-1.4 2.4-4-1.1-9.2-5.7-8.5-4.4.7-6.3 6.2-3.2 9.4 1.7 1.9 4.6 2.3 6.9 1.1.6.6 1.1 1.1 1.6 1.7.7.9 1.2 1.8 2.1 2.5.6.5 1.4 1.2 2.3 1.3 1.1.1 1.7-.6 1.7-1.6-.1-.9-1-1.9-1.6-2.5m-8.9-2.3c-2.2 0-4-1.8-4-4s1.8-4 4-4 4 1.8 4 4-1.8 4-4 4m2.1-4.8c0-.4.1-.7.1-1.2 0-.8-.4-1-1.3-1H8v.5h.3c.5 0 .7.1.7.5v1.1c0 .5.2.7.7.8-.6.2-.8.4-.8.9v1.1c.1.4-.1.5-.6.5H8v.6h.5c.9 0 1.3-.2 1.3-1 0-.5-.1-.8-.1-1.2 0-.2.2-.5.9-.5v-.6c-.7 0-.9-.3-.9-.5\"><\/path>\n<\/svg><\/div><\/div>\n\n\n\n<style>\n  \/* Minimal Blue Theme - Light Trade-off Explorer (+0.8rem Font Scale) *\/\n  .dg-blog-wrapper {\n    font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Roboto, Oxygen-Sans, Ubuntu, Cantarell, \"Helvetica Neue\", sans-serif;\n    color: #334155;\n    line-height: 1.6;\n    font-size: 1.8rem !important; \/* Base 1.0 + 0.8 *\/\n  }\n  \n  .dg-blog-wrapper h2 {\n    color: #0f172a;\n    font-size: 2.8rem !important; \/* Base 2.0 + 0.8 *\/\n    margin-top: 48px;\n    margin-bottom: 24px;\n    font-weight: 700;\n  }\n\n  .dg-blog-wrapper p {\n    margin-bottom: 20px;\n  }\n\n  \/* Trade-off Card Container (Light Theme) *\/\n  .dg-to-card {\n    background-color: #ffffff;\n    border: 1px solid #e2e8f0;\n    border-top: 4px solid #0284c7;\n    border-radius: 12px;\n    padding: 32px;\n    margin: 40px 0;\n    box-shadow: 0 10px 25px rgba(2, 132, 199, 0.05);\n  }\n\n  .dg-to-title {\n    font-size: 2.1rem !important; \/* Base 1.3 + 0.8 *\/\n    font-weight: 700;\n    margin-bottom: 4px;\n    color: #0f172a;\n  }\n\n  .dg-to-subtitle {\n    font-size: 1.7rem !important; \/* Base 0.9 + 0.8 *\/\n    color: #64748b;\n    margin-bottom: 24px;\n  }\n\n  \/* Toggle Buttons (Light Theme) *\/\n  .dg-to-toggle {\n    display: inline-flex;\n    background: #f8fafc;\n    border: 1px solid #cbd5e1;\n    border-radius: 8px;\n    overflow: hidden;\n    margin-bottom: 32px;\n    padding: 4px;\n    gap: 4px;\n  }\n\n  .dg-to-btn {\n    padding: 8px 20px;\n    font-size: 1.7rem !important; \/* Base 0.9 + 0.8 *\/\n    font-weight: 600;\n    cursor: pointer;\n    border: none;\n    outline: none;\n    border-radius: 6px;\n    transition: all 0.2s;\n  }\n\n  .dg-to-btn.active {\n    background: #0284c7;\n    color: #ffffff;\n    box-shadow: 0 2px 4px rgba(2, 132, 199, 0.2);\n  }\n\n  .dg-to-btn.inactive {\n    background: transparent;\n    color: #475569;\n  }\n  \n  .dg-to-btn.inactive:hover {\n    background: #e2e8f0;\n    color: #0f172a;\n  }\n\n  \/* Stats Row *\/\n  .dg-to-stats {\n    display: flex;\n    justify-content: space-between;\n    align-items: flex-end;\n    margin-bottom: 24px;\n    flex-wrap: wrap;\n    gap: 24px;\n  }\n\n  .dg-to-stat-col {\n    display: flex;\n    flex-direction: column;\n  }\n\n  .dg-to-stat-col.right {\n    text-align: right;\n    align-items: flex-end;\n  }\n\n  .dg-to-label {\n    font-weight: 700;\n    font-size: 1.9rem !important; \/* Base 1.1 + 0.8 *\/\n    color: #0f172a;\n  }\n\n  .dg-to-sublabel {\n    font-size: 1.6rem !important; \/* Base 0.8 + 0.8 *\/\n    color: #64748b;\n  }\n\n  .dg-to-value {\n    font-size: 3.5rem !important; \/* Base 2.7 + 0.8 *\/\n    font-weight: 800;\n    line-height: 1.1;\n    margin: 12px 0 4px 0;\n  }\n\n  \/* Adjusted colors for better contrast on white background *\/\n  .dg-to-value.orange {\n    color: #ea580c; \n  }\n\n  .dg-to-value.blue {\n    color: #0284c7; \n  }\n\n  .dg-to-details {\n    font-size: 1.6rem !important;\n    color: #475569;\n    font-weight: 500;\n  }\n\n  \/* Gradient Bar *\/\n  .dg-to-bar-area {\n    position: relative;\n    margin-top: 16px;\n    margin-bottom: 48px;\n  }\n\n  .dg-to-bar {\n    height: 18px;\n    border-radius: 9px;\n    background: linear-gradient(90deg, #ea580c, #7c3aed, #0284c7);\n    width: 100%;\n  }\n\n  \/* Operating Point Dashed Box (Darker for light theme) *\/\n  .dg-to-op-box {\n    position: absolute;\n    left: 20%;\n    right: 20%;\n    top: -8px;\n    bottom: -8px;\n    border: 2px dashed #0f172a;\n    border-radius: 8px;\n    background: rgba(255, 255, 255, 0.4);\n    box-shadow: 0 0 10px rgba(0,0,0,0.05);\n  }\n\n  .dg-to-op-label {\n    position: absolute;\n    bottom: -32px;\n    left: 0;\n    width: 100%;\n    text-align: center;\n    font-weight: 700;\n    font-size: 1.6rem !important;\n    color: #0f172a;\n  }\n\n  \/* Bottom Text Labels *\/\n  .dg-to-bar-labels {\n    display: flex;\n    justify-content: space-between;\n    font-size: 1.6rem !important;\n    color: #64748b;\n    font-weight: 500;\n    padding-bottom: 20px;\n    border-bottom: 1px solid #e2e8f0;\n  }\n\n  .dg-to-footer {\n    margin-top: 16px;\n    font-size: 1.5rem !important; \/* Base 0.7 + 0.8 *\/\n    color: #64748b;\n    line-height: 1.5;\n  }\n  \n  \/* Tab Animation *\/\n  .dg-tab-content {\n    display: none;\n    animation: fadeIn 0.3s ease-in-out;\n  }\n  .dg-tab-content.active {\n    display: block;\n  }\n  \n  @keyframes fadeIn {\n    from { opacity: 0; transform: translateY(5px); }\n    to { opacity: 1; transform: translateY(0); }\n  }\n\n  @media (max-width: 768px) {\n    .dg-to-value { font-size: 2.8rem !important; }\n    .dg-to-op-box { left: 10%; right: 10%; }\n  }\n<\/style>\n\n<div class=\"dg-blog-wrapper\">\n  \n  <h2> Two Design Boundaries: Quality vs. Efficiency<\/h2>\n\n  <p>In embedded AI, every design is a balance between image fidelity and hardware resources. The research establishes two clear boundaries: an <strong>FP32 maximum-quality reference<\/strong> and an <strong>INT8 resource-efficient deployment<\/strong>. The ideal product sits somewhere between these points.<\/p>\n\n  <!-- Light Theme Trade-off Explorer Graphic -->\n  <div class=\"dg-to-card\">\n    \n    <div class=\"dg-to-title\">Trade-off explorer<\/div>\n    <div class=\"dg-to-subtitle\">Choose a scale factor to compare the two borders.<\/div>\n\n    <!-- Tab Buttons -->\n    <div class=\"dg-to-toggle\">\n      <button type=\"button\" id=\"btn-x2\" class=\"dg-to-btn active\" onclick=\"switchTradeOffTab('x2')\">\u00d72 upscaling<\/button>\n      <button type=\"button\" id=\"btn-x4\" class=\"dg-to-btn inactive\" onclick=\"switchTradeOffTab('x4')\">\u00d74 upscaling<\/button>\n    <\/div>\n\n    <!-- TAB 1: x2 Upscaling Content -->\n    <div id=\"content-x2\" class=\"dg-tab-content active\">\n      <div class=\"dg-to-stats\">\n        <div class=\"dg-to-stat-col\">\n          <div class=\"dg-to-label\">Minimum resource<\/div>\n          <div class=\"dg-to-sublabel\">INT8 on AMD Kria\u2122 DPU<\/div>\n          <div class=\"dg-to-value orange\">29.72 dB<\/div>\n          <div class=\"dg-to-details\">SSIM 0.8698 \u00b7 0.27 MB<\/div>\n        <\/div>\n        <div class=\"dg-to-stat-col right\">\n          <div class=\"dg-to-label\">Maximum quality<\/div>\n          <div class=\"dg-to-sublabel\">FP32 full-precision reference<\/div>\n          <div class=\"dg-to-value blue\">32.56 dB<\/div>\n          <div class=\"dg-to-details\">SSIM 0.9332 \u00b7 1.10 MB<\/div>\n        <\/div>\n      <\/div>\n\n      <div class=\"dg-to-bar-area\">\n        <div class=\"dg-to-bar\"><\/div>\n        <div class=\"dg-to-op-box\">\n          <div class=\"dg-to-op-label\">Your operating point<\/div>\n        <\/div>\n      <\/div>\n\n      <div class=\"dg-to-bar-labels\">\n        <div>Smaller, lower power<\/div>\n        <div>Sharper, more memory<\/div>\n      <\/div>\n\n      <div class=\"dg-to-footer\">\n        PSNR shown. \u00d72: 64\u00d764 input tiles upscaled to 128\u00d7128. Model size estimated at 4 bytes per parameter (FP32) and 1 byte per parameter (INT8), 0.2744 M parameters.\n      <\/div>\n    <\/div>\n\n    <!-- TAB 2: x4 Upscaling Content -->\n    <div id=\"content-x4\" class=\"dg-tab-content\">\n      <div class=\"dg-to-stats\">\n        <div class=\"dg-to-stat-col\">\n          <div class=\"dg-to-label\">Minimum resource<\/div>\n          <div class=\"dg-to-sublabel\">INT8 on AMD Kria\u2122 DPU<\/div>\n          <div class=\"dg-to-value orange\">24.59 dB<\/div>\n          <div class=\"dg-to-details\">SSIM 0.6856 \u00b7 0.30 MB<\/div>\n        <\/div>\n        <div class=\"dg-to-stat-col right\">\n          <div class=\"dg-to-label\">Maximum quality<\/div>\n          <div class=\"dg-to-sublabel\">FP32 full-precision reference<\/div>\n          <div class=\"dg-to-value blue\">26.69 dB<\/div>\n          <div class=\"dg-to-details\">SSIM 0.7939 \u00b7 1.18 MB<\/div>\n        <\/div>\n      <\/div>\n\n      <div class=\"dg-to-bar-area\">\n        <div class=\"dg-to-bar\"><\/div>\n        <div class=\"dg-to-op-box\">\n          <div class=\"dg-to-op-label\">Your operating point<\/div>\n        <\/div>\n      <\/div>\n\n      <div class=\"dg-to-bar-labels\">\n        <div>Smaller, lower power<\/div>\n        <div>Sharper, more memory<\/div>\n      <\/div>\n\n      <div class=\"dg-to-footer\">\n        PSNR shown. \u00d74: 32\u00d732 input tiles upscaled to 128\u00d7128. Model sizes as reported in the paper, 0.2952 M parameters.\n      <\/div>\n    <\/div>\n\n  <\/div>\n<\/div>\n\n<!-- JavaScript \u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e23\u0e30\u0e1a\u0e1a\u0e2a\u0e25\u0e31\u0e1a Tab -->\n<script>\n  function switchTradeOffTab(tabId) {\n    var btnX2 = document.getElementById('btn-x2');\n    var btnX4 = document.getElementById('btn-x4');\n    var contentX2 = document.getElementById('content-x2');\n    var contentX4 = document.getElementById('content-x4');\n\n    if (tabId === 'x2') {\n      btnX2.className = 'dg-to-btn active';\n      btnX4.className = 'dg-to-btn inactive';\n      contentX2.className = 'dg-tab-content active';\n      contentX4.className = 'dg-tab-content';\n    } else if (tabId === 'x4') {\n      btnX2.className = 'dg-to-btn inactive';\n      btnX4.className = 'dg-to-btn active';\n      contentX2.className = 'dg-tab-content';\n      contentX4.className = 'dg-tab-content active';\n    }\n  }\n<\/script>\n\n\n\n\n<style>\n  \/* Minimal Dual Image Showcase *\/\n  .dg-dual-figure {\n    margin: 48px 0;\n    display: flex;\n    flex-direction: column;\n    align-items: center;\n    gap: 16px;\n  }\n  \n  .dg-dual-figure-grid {\n    display: grid;\n    grid-template-columns: 1fr 1fr;\n    gap: 24px;\n    width: 100%;\n    max-width: 1000px;\n  }\n  \n  .dg-dual-figure-grid img {\n    width: 100%;\n    height: auto;\n    border-radius: 8px;\n    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.08);\n    border: 1px solid #e2e8f0;\n    transition: transform 0.2s ease;\n  }\n\n  .dg-dual-figure-grid img:hover {\n    transform: scale(1.02);\n  }\n  \n  .dg-figure-caption {\n    font-size: 1.6rem !important;\n    color: #475569;\n    font-style: italic;\n    text-align: center;\n    max-width: 800px;\n    margin-top: 8px;\n  }\n  \n  @media (max-width: 768px) {\n    .dg-dual-figure-grid {\n      grid-template-columns: 1fr;\n      gap: 16px;\n    }\n  }\n<\/style>\n\n<div class=\"dg-dual-figure\">\n  <div class=\"dg-dual-figure-grid\">\n    <!-- \u0e20\u0e32\u0e1e 2X -->\n    <img decoding=\"async\" src=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/09\/2X.png\" alt=\"AERU-Net 2X upscaling results on AMD Kria KV260\">\n    <!-- \u0e20\u0e32\u0e1e 4X -->\n    <img decoding=\"async\" src=\"https:\/\/dgway.com\/blog_E\/wp-content\/uploads\/2026\/09\/4X.png\" alt=\"AERU-Net 4X upscaling results on AMD Kria KV260\">\n  <\/div>\n  <div class=\"dg-figure-caption\">\n    Visual Proof (2X &#038; 4X Upscaling): Ground truth (Left), Low resolution (Middle), and Our Optimized KV260 Result (Right)\n  <\/div>\n<\/div>\n\n\n\n\n<style>\n  \/* Image Showcase Container *\/\n  .dg-image-showcase {\n    background: #ffffff;\n    border: 1px solid #e2e8f0;\n    border-radius: 12px;\n    padding: 24px;\n    margin: 40px 0;\n    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.02);\n    text-align: center;\n  }\n\n  .dg-image-showcase img {\n    max-width: 100%;\n    height: auto;\n    border-radius: 8px;\n  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running directly on the AMD Kria\u2122 KV260 edge platform.\n  <\/p>\n<\/div>\n\n\n\n<div class=\"wp-block-boldblocks-icon-separator\" role=\"separator\"><div class=\"wp-block-boldblocks-icon-separator__inner icon-center is-align-center\" style=\"--bb-border:1px solid;--bb--icon-width:1em;--bb--icon-spacing:.5em\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" xml:space=\"preserve\" viewBox=\"0 0 20 20\">\n  <path d=\"M6.1 9.5V8.4c0-.5-.2-.7-.7-.8.6-.1.8-.3.8-.9V5.6c0-.4.1-.5.7-.5h.3v-.5h-.6c-.9 0-1.3.2-1.3 1 0 .5.1.8.1 1.2 0 .2-.2.5-.9.5v.6c.7 0 .9.3.9.5 0 .4-.1.7-.1 1.2 0 .8.4 1 1.3 1h.5V10h-.3c-.5 0-.7-.1-.7-.5m10.4 4.4c-.8-.8-1.7-1.4-2.6-2-.1-.1-1.1-1.1-1.5-1.4 2.4-4-1.1-9.2-5.7-8.5-4.4.7-6.3 6.2-3.2 9.4 1.7 1.9 4.6 2.3 6.9 1.1.6.6 1.1 1.1 1.6 1.7.7.9 1.2 1.8 2.1 2.5.6.5 1.4 1.2 2.3 1.3 1.1.1 1.7-.6 1.7-1.6-.1-.9-1-1.9-1.6-2.5m-8.9-2.3c-2.2 0-4-1.8-4-4s1.8-4 4-4 4 1.8 4 4-1.8 4-4 4m2.1-4.8c0-.4.1-.7.1-1.2 0-.8-.4-1-1.3-1H8v.5h.3c.5 0 .7.1.7.5v1.1c0 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\u0e43\u0e19\u0e21\u0e37\u0e2d\u0e16\u0e37\u0e2d\u0e43\u0e2b\u0e49\u0e01\u0e25\u0e48\u0e2d\u0e07\u0e02\u0e22\u0e32\u0e22\u0e40\u0e15\u0e47\u0e21\u0e08\u0e2d *\/\n      padding: 24px;\n    }\n  }\n<\/style>\n\n<div class=\"dg-blog-wrapper\">\n\n  <h2>Finding the Sweet Spot: Customizing for Your System<\/h2>\n\n  <div class=\"dg-intro-text\">\n    <p>For real-world deployments\u2014especially in UAVs and remote-sensing equipment\u2014the ideal AI solution must balance image fidelity against strict hardware limits. <strong>Design Gateway and MDAP can use your requirements as a starting point to engineer a customized operating point.<\/strong> Here is what we can tune:<\/p>\n  <\/div>\n\n  <div class=\"dg-category-grid\">\n\n    <!-- Category 1: Performance Targets -->\n    <div class=\"dg-cat-card\">\n      <div class=\"dg-cat-header\">\n        <div class=\"dg-cat-icon\">\n          <!-- Target\/Bullseye Icon -->\n          <svg fill=\"none\" stroke=\"currentColor\" viewBox=\"0 0 24 24\" stroke-width=\"2\"><path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M13 10V3L4 14h7v7l9-11h-7z\"><\/path><\/svg>\n        <\/div>\n        <h4 class=\"dg-cat-title\">Performance Targets<\/h4>\n      <\/div>\n      <ul class=\"dg-cat-list\">\n        <li><strong>Image Quality<\/strong> Define the acceptable reconstruction baseline.<\/li>\n        <li><strong>Upscaling Factor<\/strong> Start from \u00d72 or \u00d74 based on the application use case.<\/li>\n        <li><strong>Frame Rate<\/strong> Balance real-time throughput vs. model complexity.<\/li>\n      <\/ul>\n    <\/div>\n\n    <!-- Category 2: Hardware Limits -->\n    <div class=\"dg-cat-card\">\n      <div class=\"dg-cat-header\">\n        <div class=\"dg-cat-icon\">\n          <!-- CPU\/Hardware Icon -->\n          <svg fill=\"none\" stroke=\"currentColor\" viewBox=\"0 0 24 24\" stroke-width=\"2\"><path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 3v2m6-2v2M9 19v2m6-2v2M5 9H3m2 6H3m18-6h-2m2 6h-2M7 19h10a2 2 0 002-2V7a2 2 0 00-2-2H7a2 2 0 00-2 2v10a2 2 0 002 2zM9 9h6v6H9V9z\"><\/path><\/svg>\n        <\/div>\n        <h4 class=\"dg-cat-title\">Hardware Limits<\/h4>\n      <\/div>\n      <ul class=\"dg-cat-list\">\n        <li><strong>Memory Budget<\/strong> Tune the model to fit available on-chip and external memory.<\/li>\n        <li><strong>Power &#038; Thermal<\/strong> Optimize for continuously operated edge equipment.<\/li>\n        <li><strong>Kria\u2122 Platform<\/strong> Adapt deployment to the specific hardware I\/O environment.<\/li>\n      <\/ul>\n    <\/div>\n\n    <!-- Category 3: Model Adaptation -->\n    <div class=\"dg-cat-card\">\n      <div class=\"dg-cat-header\">\n        <div class=\"dg-cat-icon\">\n          <!-- Neural\/Data Icon -->\n          <svg fill=\"none\" stroke=\"currentColor\" viewBox=\"0 0 24 24\" stroke-width=\"2\"><path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M19 11H5m14 0a2 2 0 012 2v6a2 2 0 01-2 2H5a2 2 0 01-2-2v-6a2 2 0 012-2m14 0V9a2 2 0 00-2-2M5 11V9a2 2 0 002-2m0 0V5a2 2 0 012-2h6a2 2 0 012 2v2M7 7h10\"><\/path><\/svg>\n        <\/div>\n        <h4 class=\"dg-cat-title\">Model Adaptation<\/h4>\n      <\/div>\n      <ul class=\"dg-cat-list\">\n        <li><strong>Quantization<\/strong> Select the precision strategy (e.g., INT8) according to resource levels.<\/li>\n        <li><strong>Custom Data<\/strong> Retrain or fine-tune using imagery from your operating environment.<\/li>\n      <\/ul>\n    <\/div>\n\n  <\/div>\n\n<\/div>\n\n\n\n\n\n\n\n<div class=\"wp-block-boldblocks-icon-separator\" role=\"separator\"><div class=\"wp-block-boldblocks-icon-separator__inner icon-center is-align-center\" style=\"--bb-border:1px solid;--bb--icon-width:1em;--bb--icon-spacing:.5em\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" xml:space=\"preserve\" viewBox=\"0 0 20 20\">\n  <path d=\"M6.1 9.5V8.4c0-.5-.2-.7-.7-.8.6-.1.8-.3.8-.9V5.6c0-.4.1-.5.7-.5h.3v-.5h-.6c-.9 0-1.3.2-1.3 1 0 .5.1.8.1 1.2 0 .2-.2.5-.9.5v.6c.7 0 .9.3.9.5 0 .4-.1.7-.1 1.2 0 .8.4 1 1.3 1h.5V10h-.3c-.5 0-.7-.1-.7-.5m10.4 4.4c-.8-.8-1.7-1.4-2.6-2-.1-.1-1.1-1.1-1.5-1.4 2.4-4-1.1-9.2-5.7-8.5-4.4.7-6.3 6.2-3.2 9.4 1.7 1.9 4.6 2.3 6.9 1.1.6.6 1.1 1.1 1.6 1.7.7.9 1.2 1.8 2.1 2.5.6.5 1.4 1.2 2.3 1.3 1.1.1 1.7-.6 1.7-1.6-.1-.9-1-1.9-1.6-2.5m-8.9-2.3c-2.2 0-4-1.8-4-4s1.8-4 4-4 4 1.8 4 4-1.8 4-4 4m2.1-4.8c0-.4.1-.7.1-1.2 0-.8-.4-1-1.3-1H8v.5h.3c.5 0 .7.1.7.5v1.1c0 .5.2.7.7.8-.6.2-.8.4-.8.9v1.1c.1.4-.1.5-.6.5H8v.6h.5c.9 0 1.3-.2 1.3-1 0-.5-.1-.8-.1-1.2 0-.2.2-.5.9-.5v-.6c-.7 0-.9-.3-.9-.5\"><\/path>\n<\/svg><\/div><\/div>\n\n\n\n\n<style>\n  \/* Minimal Blue Theme - Compact Resources (+0.8rem Font Scale) *\/\n  .dg-blog-wrapper {\n    font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Roboto, Oxygen-Sans, Ubuntu, Cantarell, \"Helvetica Neue\", sans-serif;\n    color: #334155;\n    line-height: 1.6;\n    font-size: 1.8rem !important;\n  }\n\n  .dg-blog-wrapper h2 {\n    color: #0f172a;\n    font-size: 2.8rem !important;\n    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line-height: 1.3;\n  }\n\n  .dg-res-item:hover .dg-res-text {\n    color: #0369a1;\n  }\n\n  \/* --- Unified Note Box --- *\/\n  .dg-unified-note {\n    background: #f8fafc;\n    border: 1px solid #e2e8f0;\n    border-left: 4px solid #0284c7;\n    border-radius: 8px;\n    padding: 24px;\n    margin-bottom: 40px;\n    font-size: 1.65rem !important;\n    color: #475569;\n  }\n\n  .dg-unified-note strong {\n    color: #0f172a;\n  }\n\n  .dg-unified-note a {\n    color: #0284c7;\n    font-weight: 600;\n    text-decoration: underline;\n    text-underline-offset: 4px;\n  }\n\n  .dg-unified-note a:hover {\n    color: #0369a1;\n  }\n\n  \n  \/* CTA Banner (Integrated) *\/\n  .dg-cta-banner {\n    background: #f0f9ff;\n    border: 1px solid #bae6fd;\n    border-radius: 12px;\n    padding: 32px;\n    text-align: center;\n  }\n\n  .dg-cta-banner h3 {\n    margin-top: 0;\n    margin-bottom: 24px;\n    font-size: 2.2rem !important;\n    color: #0f172a;\n  }\n\n  .dg-btn-group {\n    display: flex;\n    flex-wrap: wrap;\n    justify-content: center;\n    gap: 20px;\n  }\n\n  .dg-btn {\n    display: inline-flex;\n    align-items: center;\n    justify-content: center;\n    padding: 14px 32px;\n    border-radius: 9999px;\n    font-size: 1.9rem !important;\n    font-weight: 700;\n    text-decoration: none;\n    transition: all 0.2s ease;\n    cursor: pointer;\n  }\n\n  .dg-btn-primary {\n    background-color: #75c9fa; \n    color: #0369a1;\n    border: 2px solid #75c9fa;\n  }\n\n  .dg-btn-primary:hover {\n    background-color: #2db1fc;\n    border-color: #2db1fc;\n    color: #0f172a;\n  }\n\n  .dg-btn-secondary {\n    background-color: #ffffff;\n    color: #0284c7;\n    border: 2px solid #0284c7;\n  }\n\n  .dg-btn-secondary:hover {\n    background-color: #e0f2fe;\n    color: #0369a1;\n  }\n<\/style>\n\n<div class=\"dg-blog-wrapper\">\n\n  <h2>Learn More About AERU-Net &amp; Kria\u2122 Edge AI<\/h2>\n\n  <!-- Compact Resource Links -->\n  <div class=\"dg-resource-list\">\n    \n    <a href=\"https:\/\/dgway.com\/blog_E\/2026\/06\/05\/sharpening-the-view-from-orbit-aeru-nets-adaptive-edge-recovery-approach-to-satellite-image-super-resolution\/\" target=\"_blank\" rel=\"noopener\" class=\"dg-res-item\">\n      <div class=\"dg-res-icon\">\n        <svg fill=\"none\" stroke=\"currentColor\" viewBox=\"0 0 24 24\" stroke-width=\"2\"><path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M10 6H6a2 2 0 00-2 2v10a2 2 0 002 2h10a2 2 0 002-2v-4M14 4h6m0 0v6m0-6L10 14\"><\/path><\/svg>\n      <\/div>\n      <div class=\"dg-res-text\">AERU-Net Algorithm Overview \u2014 Design Gateway Blog<\/div>\n    <\/a>\n\n    <a href=\"https:\/\/www.cuee-mdap.co\/\" target=\"_blank\" rel=\"noopener\" class=\"dg-res-item\">\n      <div class=\"dg-res-icon\">\n        <svg fill=\"none\" stroke=\"currentColor\" viewBox=\"0 0 24 24\" stroke-width=\"2\"><path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M21 12a9 9 0 01-9 9m9-9a9 9 0 00-9-9m9 9H3m9 9a9 9 0 01-9-9m9 9c1.657 0 3-4.03 3-9s-1.343-9-3-9m0 18c-1.657 0-3-4.03-3-9s1.343-9 3-9m-9 9a9 9 0 019-9\"><\/path><\/svg>\n      <\/div>\n      <div class=\"dg-res-text\">CUEE MDAP Research Unit<\/div>\n    <\/a>\n\n    <a href=\"https:\/\/www.cuee-mdap.co\/post\/announcement-of-collaboration-for-ai-ip-core-technology-development-between-design-gateway-and-mdap\" target=\"_blank\" rel=\"noopener\" class=\"dg-res-item\">\n      <div class=\"dg-res-icon\">\n        <svg fill=\"none\" stroke=\"currentColor\" viewBox=\"0 0 24 24\" stroke-width=\"2\"><path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M19 20H5a2 2 0 01-2-2V6a2 2 0 012-2h10a2 2 0 012 2v1m2 13a2 2 0 01-2-2V7m2 13a2 2 0 002-2V9a2 2 0 00-2-2h-2m-4-3H9M7 16h6M7 8h6v4H7V8z\"><\/path><\/svg>\n      <\/div>\n      <div class=\"dg-res-text\">MDAP \u00d7 Design Gateway Partnership<\/div>\n    <\/a>\n\n    <a href=\"https:\/\/doi.org\/10.1109\/ISMAC65024.2025.11175925\" target=\"_blank\" rel=\"noopener\" class=\"dg-res-item\">\n      <div class=\"dg-res-icon\">\n        <svg fill=\"none\" stroke=\"currentColor\" viewBox=\"0 0 24 24\" stroke-width=\"2\"><path stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z\"><\/path><\/svg>\n      <\/div>\n      <div class=\"dg-res-text\">Full Research Paper: Edge AI Super-Resolution (IEEE)<\/div>\n    <\/a>\n\n  <\/div>\n\n  <!-- Unified Note Box -->\n  <div class=\"dg-unified-note\">\n    <strong>Note:<\/strong> Note: Performance metrics shown are based on specific research configurations using the AMD Kria\u2122 KV260. As we move from research to real FPGA edge hardware, commercial results will vary. To evaluate the model or optimize the solution for your specific constraints\u2014such as image quality, frame rate, memory budget, and target platform\u2014please <a href=\"https:\/\/dgway.com\/contact.html\" target=\"_blank\" rel=\"noopener\">contact Design Gateway<\/a>.\n  <\/div>\n\n\n<\/div>\n\n\n\n\n\n<style>\n  \/* Minimal Partnership & CTA Banner (Modern Red & White Theme) *\/\n  .dg-partner-cta {\n    background: #f2f2f2;\n    border: 1px solid #e2e8f0;\n    border-top: 4px solid #69c7fa; \/* Accent Red *\/\n    border-radius: 12px;\n    padding: 48px 40px;\n    text-align: center;\n    margin: 48px 0;\n    box-shadow: 0 10px 25px rgba(0, 0, 0, 0.04);\n  }\n  \n  .dg-partner-cta-logos {\n    display: flex;\n    align-items: center;\n    justify-content: center;\n    gap: 16px;\n    margin-bottom: 24px;\n    font-size: 2rem !important;\n  }\n  \n  .dg-partner-cta-logos .mdap-text {\n    font-weight: 700;\n    color: #000000;\n  }\n  \n  .dg-partner-cta-logos .plus {\n    font-weight: 800;\n    color: #69c7fa;\n    font-size: 2.4rem;\n  }\n  \n  .dg-partner-cta-logos .dg-text {\n    font-weight: 700;\n    color: #000000;\n  }\n  \n  .dg-partner-cta h3 {\n    margin-top: 0;\n    margin-bottom: 16px;\n    font-size: 2.6rem !important;\n    color: #0f172a;\n    font-weight: 700;\n  }\n  \n  .dg-partner-cta p {\n    font-size: 1.8rem !important;\n    color: #475569;\n    max-width: 800px;\n    margin: 0 auto 32px auto;\n    line-height: 1.6;\n  }\n  \n\n  \n  @media (max-width: 768px) {\n    .dg-partner-cta-logos {\n      flex-direction: column;\n      gap: 8px;\n    }\n    .dg-btn-group {\n      flex-direction: column;\n    }\n    .dg-btn {\n      width: 100%;\n    }\n    .dg-partner-cta {\n      padding: 32px 24px;\n    }\n  }\n<\/style>\n\n<div class=\"dg-blog-wrapper\">\n  <div class=\"dg-partner-cta\">\n    \n    <!-- Partnership Text Header -->\n    <div class=\"dg-partner-cta-logos\">\n      <span class=\"mdap-text\">CUEE MDAP Research<\/span>\n      <span class=\"plus\">\u00d7<\/span>\n      <span class=\"dg-text\">Design Gateway<\/span>\n    <\/div>\n    \n    <h3>From Concept to Real-World Edge Hardware<\/h3>\n    <p>Bringing AERU-Net from an AI concept to a commercial FPGA deployment requires balancing image fidelity against strict hardware limits. <strong>Tell us your constraints, and we will help engineer the right design.<\/strong><\/p>\n    \n    <!-- Action Buttons -->\n    <div class=\"dg-btn-group\">\n      <a href=\"https:\/\/dgway.com\/contact.html\" target=\"_blank\" rel=\"noopener\" class=\"dg-btn dg-btn-primary\">Contact Design Gateway<\/a>\n      <a href=\"https:\/\/www.cuee-mdap.co\/\" target=\"_blank\" rel=\"noopener\" class=\"dg-btn dg-btn-secondary\">Visit CUEE MDAP<\/a>\n    <\/div>\n    \n  <\/div>\n<\/div>\n\n\n\n\n<div class=\"wp-block-boldblocks-icon-separator\" role=\"separator\"><div class=\"wp-block-boldblocks-icon-separator__inner icon-center is-align-center\" style=\"--bb-border:1px solid;--bb--icon-width:1em;--bb--icon-spacing:.5em\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" xml:space=\"preserve\" viewBox=\"0 0 20 20\">\n  <path d=\"M6.1 9.5V8.4c0-.5-.2-.7-.7-.8.6-.1.8-.3.8-.9V5.6c0-.4.1-.5.7-.5h.3v-.5h-.6c-.9 0-1.3.2-1.3 1 0 .5.1.8.1 1.2 0 .2-.2.5-.9.5v.6c.7 0 .9.3.9.5 0 .4-.1.7-.1 1.2 0 .8.4 1 1.3 1h.5V10h-.3c-.5 0-.7-.1-.7-.5m10.4 4.4c-.8-.8-1.7-1.4-2.6-2-.1-.1-1.1-1.1-1.5-1.4 2.4-4-1.1-9.2-5.7-8.5-4.4.7-6.3 6.2-3.2 9.4 1.7 1.9 4.6 2.3 6.9 1.1.6.6 1.1 1.1 1.6 1.7.7.9 1.2 1.8 2.1 2.5.6.5 1.4 1.2 2.3 1.3 1.1.1 1.7-.6 1.7-1.6-.1-.9-1-1.9-1.6-2.5m-8.9-2.3c-2.2 0-4-1.8-4-4s1.8-4 4-4 4 1.8 4 4-1.8 4-4 4m2.1-4.8c0-.4.1-.7.1-1.2 0-.8-.4-1-1.3-1H8v.5h.3c.5 0 .7.1.7.5v1.1c0 .5.2.7.7.8-.6.2-.8.4-.8.9v1.1c.1.4-.1.5-.6.5H8v.6h.5c.9 0 1.3-.2 1.3-1 0-.5-.1-.8-.1-1.2 0-.2.2-.5.9-.5v-.6c-.7 0-.9-.3-.9-.5\"><\/path>\n<\/svg><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>A super-resolution model can look excellent on a GPU. The real challenge starts when the same capability must operate inside a UAV, remote-sensing payload, or compact edge system. In these applications, high-resolution imagery is valuable, but the hardware budget is limited. Memory, power consumption, heat, processing latency, and board size all become part of the AI design. The best algorithm&#46;&#46;&#46;<\/p>\n","protected":false},"author":1,"featured_media":3626,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[17],"tags":[836,1065,1064,127,863,271,1063,40,317,238,144,1031],"class_list":["post-3564","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-fpga-ai","tag-ai-image-enhancement","tag-amd","tag-amd-kria-kv260","tag-design-gateway","tag-edge-ai","tag-edge-computing","tag-edge-vision","tag-fpga","tag-fpga-acceleration","tag-hardware-acceleration","tag-high-performance-computing","tag-image-super-resolution"],"_links":{"self":[{"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/posts\/3564","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/comments?post=3564"}],"version-history":[{"count":80,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/posts\/3564\/revisions"}],"predecessor-version":[{"id":3671,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/posts\/3564\/revisions\/3671"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/media\/3626"}],"wp:attachment":[{"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/media?parent=3564"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/categories?post=3564"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dgway.com\/blog_E\/wp-json\/wp\/v2\/tags?post=3564"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}