{"id":7742,"date":"2021-02-03T17:03:49","date_gmt":"2021-02-03T17:03:49","guid":{"rendered":"http:\/\/ismiletechnologies.com\/?p=7742"},"modified":"2022-12-09T01:16:18","modified_gmt":"2022-12-08T19:46:18","slug":"introduction-to-cnn-implementation","status":"publish","type":"post","link":"https:\/\/ismiletechnologies.com\/en_us\/cloud\/introduction-to-cnn-implementation\/","title":{"rendered":"INTRODUCTION TO CNN IMPLEMENTATION"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"7742\" class=\"elementor elementor-7742\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-0a3dbf1 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0a3dbf1\" 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-1bab4ea\" data-id=\"1bab4ea\" 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-a8d62ec elementor-widget elementor-widget-text-editor\" data-id=\"a8d62ec\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: justify; margin: 12.0pt 0cm 12.0pt 0cm;\"><span style=\"font-size: 13.0pt; color: black; background: white;\">The first thing that comes to mind about image classification and recognition is how it works. Image classification is classifying the images in given categories based on their characteristics. Now, let&#8217;s talk about how these characteristics are extracted from the images. Here, CNN comes into play. CNN stands for Convolutional Neural Network, which is a type of deep learning neural network. CNN is mainly used for image analysis, image segmentation, and image classification, etc. Although it has the potential to do limitless work in several science fields.<\/span><\/p><p><strong>Cat Feature Extraction<\/strong><\/p><p>CNN has several layers such as convolution layer, pooling layer, Fully Connected layer, Dense layer, etc. The convolution layer is responsible for extracting features from the images on the basis of which the classification is done. The work of pooling layers is to reduce the parameters of the image. All these layers connected together help in classifying an image.<\/p>\t\t\t\t\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<section class=\"elementor-section elementor-top-section elementor-element elementor-element-63d6995 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"63d6995\" 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-4b0a370\" data-id=\"4b0a370\" 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-a735a9c elementor-widget elementor-widget-text-editor\" data-id=\"a735a9c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t\t\t\t\t\t<p>As a beginner, Keras can help you to quickly start your deep learning career. Keras is a deep learning API written in Python. You should have the basic knowledge about how to import necessary libraries like NumPy, pandas, and matplotlib.\u00a0<\/p><p>These important steps will help you to implement CNN:<\/p><ol><li>Import necessary libraries.<\/li><li>Load the Dataset.<\/li><li>Perform Data Augmentation.<\/li><li>Define and compile Keras CNN models like VGG, ResNet, InceptionNet, etc.<\/li><li>Train the model.<\/li><li>Evaluate Keras Model.<\/li><li>Make Predictions.<\/li><\/ol><p>\u00a0<\/p>\t\t\t\t\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<section class=\"elementor-section elementor-top-section elementor-element elementor-element-4f3d4d7 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"4f3d4d7\" 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-2dfc183\" data-id=\"2dfc183\" 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-2a258e9 elementor-widget elementor-widget-author-box\" data-id=\"2a258e9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"author-box.default\">\n\t\t\t\t\t\t\t<div class=\"elementor-author-box\">\n\t\t\t\n\t\t\t<div class=\"elementor-author-box__text\">\n\t\t\t\t\t\t\t\t\t<div >\n\t\t\t\t\t\t<h4 class=\"elementor-author-box__name\">\n\t\t\t\t\t\t\tSuhail Ahmed\t\t\t\t\t\t<\/h4>\n\t\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-author-box__bio\">\n\t\t\t\t\t\t<p>Data Scientist<\/p>\n\t\t\t\t\t<\/div>\n\t\t\t\t\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\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>The first thing that comes to mind about image classification and recognition is how it works. Image classification is classifying the images in given categories based on their characteristics. Now, let&#8217;s talk about how these characteristics are extracted from the images. Here, CNN comes into play. CNN stands for Convolutional Neural Network, which is a [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[97],"tags":[],"class_list":["post-7742","post","type-post","status-publish","format-standard","hentry","category-cloud"],"_links":{"self":[{"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/posts\/7742","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/comments?post=7742"}],"version-history":[{"count":5,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/posts\/7742\/revisions"}],"predecessor-version":[{"id":36096,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/posts\/7742\/revisions\/36096"}],"wp:attachment":[{"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/media?parent=7742"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/categories?post=7742"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ismiletechnologies.com\/en_us\/wp-json\/wp\/v2\/tags?post=7742"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}