{"id":4430,"date":"2011-06-22T13:50:01","date_gmt":"2011-06-22T13:50:01","guid":{"rendered":"http:\/\/hgpu.org\/?p=4430"},"modified":"2011-06-22T13:50:01","modified_gmt":"2011-06-22T13:50:01","slug":"accelerated-realization-method-of-infrared-targets-detection-based-on-gpu","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=4430","title":{"rendered":"Accelerated realization method of infrared targets detection based on GPU"},"content":{"rendered":"<p>With the rapid development of infrared detector, Realtime detection of infrared targets faces biggish challenge; In the Infrared System with detector of more cells and higher frame speed, when using more complicated processing arithmetic, the Signal Processing Platform basing on the trad framework has met hardly the demand of System&#8217;s Real-Time Detecting; the GPU for the general processing has the rapid development, provides the new type operation platform of the development foreground. Accelerating realization of infrared targets detection with GPU has more times exaltation of efficiency than realization of infrared targets detection with the tra hardware platform; it provides the research way with foreground for facing new challenge in infrared targets real-time detection.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>With the rapid development of infrared detector, Realtime detection of infrared targets faces biggish challenge; In the Infrared System with detector of more cells and higher frame speed, when using more complicated processing arithmetic, the Signal Processing Platform basing on the trad framework has met hardly the demand of System&#8217;s Real-Time Detecting; the GPU for [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[73,3,41],"tags":[1791,1789],"class_list":["post-4430","post","type-post","status-publish","format-standard","hentry","category-computer-vision","category-paper","category-signal-processing","tag-computer-vision","tag-signal-processing"],"views":1828,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4430","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=4430"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4430\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4430"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4430"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4430"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}