{"id":152,"date":"2017-06-12T20:40:43","date_gmt":"2017-06-12T20:40:43","guid":{"rendered":"http:\/\/bskog.com\/ai\/?p=152"},"modified":"2018-09-06T05:17:50","modified_gmt":"2018-09-06T05:17:50","slug":"paper-introduction-to-convolutional-nerual-networks-by-jianxin-wu","status":"publish","type":"post","link":"http:\/\/bskog.com\/ai\/2017\/06\/12\/paper-introduction-to-convolutional-nerual-networks-by-jianxin-wu\/","title":{"rendered":"Paper: Introduction to Convolutional Nerual Networks by Jianxin Wu"},"content":{"rendered":"<p>In this recently published paper, Jianxin Wu helps the reader understand<br \/>\nhow a CNN runs at the mathematical level. It is self contained and you should not need any further material to understand it from a mathematical viewpoint.<\/p>\n<p>With CNN, the important part is understanding what happens when you adjust the different parameters. Bu in order to make sense of those it is much easier when you know the underlying principles behind it.<\/p>\n<p><a href=\"https:\/\/pdfs.semanticscholar.org\/450c\/a19932fcef1ca6d0442cbf52fec38fb9d1e5.pdf\">Here you go<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this recently published paper, Jianxin Wu helps the reader understand how a CNN runs at the mathematical level. It is self contained and you should not need any further material to understand it from a mathematical viewpoint. With CNN, the important part is understanding what happens when you adjust the different parameters. Bu in &hellip; <\/p>\n<p class=\"link-more\"><a href=\"http:\/\/bskog.com\/ai\/2017\/06\/12\/paper-introduction-to-convolutional-nerual-networks-by-jianxin-wu\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Paper: Introduction to Convolutional Nerual Networks by Jianxin Wu&#8221;<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,20,25],"tags":[],"class_list":["post-152","post","type-post","status-publish","format-standard","hentry","category-deep-learning","category-neural-nets","category-papers"],"_links":{"self":[{"href":"http:\/\/bskog.com\/ai\/wp-json\/wp\/v2\/posts\/152","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/bskog.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/bskog.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/bskog.com\/ai\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/bskog.com\/ai\/wp-json\/wp\/v2\/comments?post=152"}],"version-history":[{"count":1,"href":"http:\/\/bskog.com\/ai\/wp-json\/wp\/v2\/posts\/152\/revisions"}],"predecessor-version":[{"id":503,"href":"http:\/\/bskog.com\/ai\/wp-json\/wp\/v2\/posts\/152\/revisions\/503"}],"wp:attachment":[{"href":"http:\/\/bskog.com\/ai\/wp-json\/wp\/v2\/media?parent=152"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/bskog.com\/ai\/wp-json\/wp\/v2\/categories?post=152"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/bskog.com\/ai\/wp-json\/wp\/v2\/tags?post=152"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}