{"id":9347,"date":"2026-09-24T11:22:08","date_gmt":"2026-09-24T04:22:08","guid":{"rendered":"https:\/\/www.infra-corp.co\/?p=9347"},"modified":"2026-09-24T11:32:28","modified_gmt":"2026-09-24T04:32:28","slug":"yol026-rd-an-end-to-end-road-damage-detection-network-with-learnable-contrast-enhancement-and-edge-guided-downsampling","status":"publish","type":"post","link":"https:\/\/www.infra-corp.co\/en\/yol026-rd-an-end-to-end-road-damage-detection-network-with-learnable-contrast-enhancement-and-edge-guided-downsampling\/","title":{"rendered":"YOL026-RD: An End-to-End Road Damage Detection Network With Learnable Contrast Enhancement and Edge-Guided Downsampling"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"9347\" class=\"elementor elementor-9347 elementor-9337\" data-elementor-settings=\"{&quot;element_pack_global_tooltip_width&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_width_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_width_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;size&quot;:&quot;&quot;,&quot;sizes&quot;:[]},&quot;element_pack_global_tooltip_padding&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_padding_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_padding_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius_tablet&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true},&quot;element_pack_global_tooltip_border_radius_mobile&quot;:{&quot;unit&quot;:&quot;px&quot;,&quot;top&quot;:&quot;&quot;,&quot;right&quot;:&quot;&quot;,&quot;bottom&quot;:&quot;&quot;,&quot;left&quot;:&quot;&quot;,&quot;isLinked&quot;:true}}\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-1492738 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1492738\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-fa4db3f\" data-id=\"fa4db3f\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-70e756e elementor-widget elementor-widget-text-editor\" data-id=\"70e756e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-size: 12pt; color: #000000;\"><strong>Research Title : <\/strong>YOL026-RD: An End-to-End Road Damage Detection Network With Learnable Contrast Enhancement and Edge-Guided Downsampling<\/span><\/p><p><span style=\"font-size: 12pt; color: #000000;\"><strong>Co-Researchers : <\/strong>Dr. Pawarotorn Chaipetch Miss Hathairat Samaikul and Mr. Theerayut Yonseng<\/span><\/p><p><span style=\"font-size: 12pt; color: #000000;\">The study investigates limitations of road damage detection systems applied to road survey imagery. Some damage instances are small relative to the image resolution, while <strong>Stride-4<\/strong> downsampling can result in localization errors.<\/span><\/p><p><span style=\"font-size: 12pt; color: #000000;\">The researchers developed <strong>YOL026-RD<\/strong> by modifying the <strong>Detection Head<\/strong>, adding <strong>Learnable Contrast Enhancement<\/strong>, a module that learns its parameters from the detection loss, and <strong>EdgeSPD<\/strong>, a spatially lossless downsampler guided by a <strong>Sobel Prior<\/strong>.<\/span><\/p><p><span style=\"font-size: 12pt; color: #000000;\">In the experiments, YOL026-RD achieved an average <strong>mAP50 of 0.790<\/strong> and <strong>mAP50-95 of 0.482<\/strong> across five scales. It also achieved <strong>98 frames per second<\/strong> on an entry-level accelerator at survey speeds of <strong>21\u2013100 km\/h<\/strong>.<\/span><\/p><p><span style=\"font-size: 12pt; color: #000000;\">The research uses road-condition survey imagery captured by a camera mounted above the pavement and continuously recording frames. The detected information includes <strong>damage class, bounding box, confidence, timestamp, and position of each detected distress<\/strong>.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>This research presents YOL026-RD, a network for detecting road surface damage from survey imagery. It incorporates Learnable Contrast Enhancement and Edge-Guided Downsampling to improve the detection of small-scale damage and preserve image details during processing.<\/p>\n","protected":false},"author":2,"featured_media":9339,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[73],"tags":[149,109],"class_list":["post-9347","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research-videos","tag-research-videos","tag--en"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>YOL026-RD: An End-to-End Road Damage Detection Network With Learnable Contrast Enhancement and Edge-Guided Downsampling - iNFRA<\/title>\n<meta name=\"description\" content=\"YOL026-RD research on road damage detection from survey imagery using Learnable Contrast Enhancement 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