{"id":6157,"date":"2011-11-03T17:54:51","date_gmt":"2011-11-03T15:54:51","guid":{"rendered":"http:\/\/hgpu.org\/?p=6157"},"modified":"2011-11-03T17:54:51","modified_gmt":"2011-11-03T15:54:51","slug":"a-mutable-hardware-abstraction-to-replace-threads","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=6157","title":{"rendered":"A Mutable Hardware Abstraction to Replace Threads"},"content":{"rendered":"<p>Ever since first digital images appeared, computer scientists all over the world have been trying to computationally estimate their similarity. So far, no solution as good as human brain was found. This paper presents another technique that tackles with this issue, using singular value decomposition &#8211; a matrix factorization method which extracts main features of the data. In addition to technique description, paper also offers some experimental results obtained using this method. These experiments show that presented technique produces satisfying results, which means it may be used to solve the image similarity puzzle.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Ever since first digital images appeared, computer scientists all over the world have been trying to computationally estimate their similarity. So far, no solution as good as human brain was found. This paper presents another technique that tackles with this issue, using singular value decomposition &#8211; a matrix factorization method which extracts main features of [&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":[36,33,3],"tags":[1787,288,1786,261],"class_list":["post-6157","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-image-processing","category-paper","tag-algorithms","tag-factorization","tag-image-processing","tag-mapreduce"],"views":2017,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6157","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=6157"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/6157\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6157"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6157"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6157"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}