{"id":6923,"date":"2024-11-06T16:35:20","date_gmt":"2024-11-06T15:35:20","guid":{"rendered":"https:\/\/www.artea.com\/what-are-convolutional-neural-networks\/"},"modified":"2026-09-29T09:29:47","modified_gmt":"2026-09-29T07:29:47","slug":"what-are-convolutional-neural-networks","status":"publish","type":"post","link":"https:\/\/www.artea.com\/en\/what-are-convolutional-neural-networks\/","title":{"rendered":"WHAT ARE CONVOLUTIONAL NEURAL NETWORKS?"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"6923\" class=\"elementor elementor-6923 elementor-5339\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-55321cfa post-content elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"55321cfa\" 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-7ba13a44\" data-id=\"7ba13a44\" 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<section class=\"elementor-section elementor-inner-section elementor-element elementor-element-70e2320e elementor-section-full_width elementor-section-height-default elementor-section-height-default\" data-id=\"70e2320e\" 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-50 elementor-inner-column elementor-element elementor-element-537c7743\" data-id=\"537c7743\" 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-719fc151 elementor-widget__width-initial elementor-widget elementor-widget-text-editor\" data-id=\"719fc151\" 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><strong>Convolutional neural networks (CNNs)<\/strong> are a specific type of <a href=\"https:\/\/www.artea.com\/en\/what-are-neural-networks\/\">neural network<\/a> designed to <strong>process data with a grid-like structure, such as images or videos<\/strong>.<\/p><p>This architecture has revolutionized the field of computer vision thanks to its ability to recognize complex patterns with extreme accuracy. CNNs are particularly well-suited for image and object recognition, but they are also used in other fields of artificial intelligence. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-213e6b1 elementor-widget elementor-widget-html\" data-id=\"213e6b1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-556bb69a elementor-widget elementor-widget-heading\" data-id=\"556bb69a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">How Convolutional Neural Networks Work<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ca50b1b elementor-widget elementor-widget-text-editor\" data-id=\"ca50b1b\" 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>Convolutional neural networks are composed of several layers, each of which plays a specific role in the learning process. The main layers of a CNN are: <\/p><p> <\/p><ul><li><strong>Convolutional Layer:<\/strong> This layer applies a series of filters (kernels) to the input image, producing activation maps that highlight salient features, such as edges, textures, or colors. The filters operate hierarchically: the first layers detect low-level features, such as edges or simple textures, while deeper layers identify more complex and abstract features. Convolution allows CNNs to reduce the dimensionality of the image while preserving relevant information.  <\/li><li><strong>Pooling Layer:<\/strong> This layer is designed to further reduce the dimensionality of the data, retaining only the most important features. There are two main pooling techniques: max pooling, which selects the maximum value from each subregion, and average pooling, which calculates the average. Pooling reduces the number of parameters and makes the model more efficient, thereby reducing the risk of overfitting.  <\/li><li><strong>Fully Connected Layer:<\/strong> In the final part of the network, the fully connected layers take the information extracted from the previous layers and use it to classify the input. Each neuron in these layers is connected to all the neurons in the previous layer, enabling the model to make complex decisions. <\/li><\/ul><p><br>CNNs use nonlinear activation functions, such as ReLU (Rectified Linear Unit), which introduce nonlinearity into the model and allow it to learn more sophisticated representations. Although other activation functions exist, such as the sigmoid or tanh, ReLU is widely preferred for its optimized performance in reducing gradient vanishing issues. <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-32825cea elementor-widget elementor-widget-image\" data-id=\"32825cea\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"800\" height=\"534\" src=\"https:\/\/www.artea.com\/wp-content\/uploads\/2024\/10\/reti-neurali-convoluzionali-1024x683.jpg\" class=\"attachment-large size-large wp-image-5347\" alt=\"\" srcset=\"https:\/\/www.artea.com\/wp-content\/uploads\/2024\/10\/reti-neurali-convoluzionali-1024x683.jpg 1024w, https:\/\/www.artea.com\/wp-content\/uploads\/2024\/10\/reti-neurali-convoluzionali-300x200.jpg 300w, https:\/\/www.artea.com\/wp-content\/uploads\/2024\/10\/reti-neurali-convoluzionali-768x512.jpg 768w, https:\/\/www.artea.com\/wp-content\/uploads\/2024\/10\/reti-neurali-convoluzionali-1536x1024.jpg 1536w, https:\/\/www.artea.com\/wp-content\/uploads\/2024\/10\/reti-neurali-convoluzionali-2048x1365.jpg 2048w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-73a95b80 elementor-widget elementor-widget-heading\" data-id=\"73a95b80\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Applications of Convolutional Neural Networks<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-977e7d2 elementor-widget elementor-widget-text-editor\" data-id=\"977e7d2\" 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>Convolutional neural networks have a wide range of applications in various fields, including:<\/p><p> <\/p><ol><li><strong>Image Classification:<br\/><\/strong>CNNs are used to classify images into different categories, such as recognizing animals, objects, or natural scenes. A practical example is the use of CNNs in e-commerce platforms, where they are used to automatically classify products based on their images, improving efficiency in cataloging thousands of items. <\/li><li><strong>Object Recognition:<br\/><\/strong>CNNs can be trained to recognize and locate specific objects within an image. For example, in self-driving cars, CNNs are used to identify pedestrians, traffic signs, and other vehicles in real time. This technology also underpins surveillance software that recognizes objects or people in complex scenarios.  <\/li><li><strong>Computer Vision for Medical Diagnostics:<br\/><\/strong>Convolutional neural networks are also used in the medical field, for example, to analyze radiological images and diagnose diseases. A practical example is the use of CNNs to analyze MRI and CT scans, which can indicate the presence of probable tumors and other tissue abnormalities with a level of accuracy that reduces the margin of error compared to traditional methods, thereby improving the effectiveness of diagnoses. <\/li><li><strong>Text Recognition (OCR):<br\/><\/strong>CNNs are also used for OCR (Optical Character Recognition), which allows images containing text to be converted into data that can be read and edited by a computer. A common example is the use of CNNs for document digitization: CNN-based OCR models can recognize and convert handwritten or printed text into digitally readable characters, thereby automating document archiving and retrieval processes. <\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-119e41a9 elementor-widget elementor-widget-heading\" data-id=\"119e41a9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Advantages and Limitations of CNNs<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-44c2a874 elementor-widget elementor-widget-text-editor\" data-id=\"44c2a874\" 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>CNNs offer numerous advantages, including the ability to reduce the need for manual image preprocessing thanks to their inherent ability to automatically filter features from the data. However, CNNs require a large amount of data to be trained effectively and can be computationally expensive, making it necessary to use GPUs to accelerate the learning process. Another important limitation is the \u201cvanishing gradient\u201d problem, which, while less critical in CNNs than in other deep networks, can still slow down or hinder the optimization process in very complex networks.  <\/p><p><br><\/p>\n<p>Convolutional neural networks represent <strong>one of the most advanced and powerful technologies in the field of artificial intelligence<\/strong>. Thanks to their structure and ability to learn hierarchical representations of data, CNNs have opened up new possibilities in numerous sectors, from computer vision to the medical industry. In addition to image processing, CNNs are finding applications in fields such as robotics and autonomous driving. With the continuous evolution of AI, we are likely to see more and more applications of CNNs even in areas that remain unexplored today.   <\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-96db427 elementor-widget elementor-widget-heading\" data-id=\"96db427\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Explore the future of your business with artea.com<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-11db41e elementor-widget elementor-widget-text-editor\" data-id=\"11db41e\" 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>In the age of intelligent automation and data-driven solutions, developing expertise in neural networks is essential to maintaining a competitive edge. If your company is ready to capitalize on the opportunities offered by machine learning and AI, <strong>artea.com<\/strong> is the right partner to support you. <\/p><p><br><\/p>\n<p>Thanks to our team of experts in systems integration, data engineering, and cutting-edge AI technologies, we offer consulting services and customized solutions to turn your data into concrete actions. From designing complex infrastructures to developing advanced algorithms, we\u2019re here to help you unlock the full value of your data. <\/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<div class=\"elementor-column elementor-col-50 elementor-inner-column elementor-element elementor-element-3b92dbf\" data-id=\"3b92dbf\" 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-1955dc8e elementor-widget elementor-widget-heading\" data-id=\"1955dc8e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-heading-title elementor-size-default\">Share this article<\/div>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5fa5481 elementor-share-buttons--skin-minimal art-share-social elementor-share-buttons--view-icon-text elementor-share-buttons--shape-square elementor-grid-0 elementor-share-buttons--color-official elementor-widget elementor-widget-global elementor-global-6594 elementor-global-3115 elementor-widget-share-buttons\" data-id=\"5fa5481\" data-element_type=\"widget\" data-e-type=\"widget\" data-settings=\"{&quot;share_url&quot;:{&quot;url&quot;:&quot;&quot;,&quot;is_external&quot;:&quot;&quot;,&quot;nofollow&quot;:&quot;&quot;,&quot;custom_attributes&quot;:&quot;&quot;}}\" data-widget_type=\"share-buttons.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-grid\" role=\"list\">\n\t\t\t\t\t\t\t\t<div class=\"elementor-grid-item\" role=\"listitem\">\n\t\t\t\t\t\t<div class=\"elementor-share-btn elementor-share-btn_twitter\" role=\"button\" tabindex=\"0\" aria-label=\"Share on twitter\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-share-btn__icon\">\n\t\t\t\t\t\t\t\t<i class=\"fab fa-twitter\" aria-hidden=\"true\"><\/i>\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-share-btn__text\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-share-btn__title\">\n\t\t\t\t\t\t\t\t\t\tTwitter\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-grid-item\" role=\"listitem\">\n\t\t\t\t\t\t<div class=\"elementor-share-btn elementor-share-btn_facebook\" role=\"button\" tabindex=\"0\" aria-label=\"Share on facebook\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-share-btn__icon\">\n\t\t\t\t\t\t\t\t<i class=\"fab fa-facebook\" aria-hidden=\"true\"><\/i>\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-share-btn__text\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-share-btn__title\">\n\t\t\t\t\t\t\t\t\t\tFacebook\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-grid-item\" role=\"listitem\">\n\t\t\t\t\t\t<div class=\"elementor-share-btn elementor-share-btn_linkedin\" role=\"button\" tabindex=\"0\" aria-label=\"Share on linkedin\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-share-btn__icon\">\n\t\t\t\t\t\t\t\t<i class=\"fab fa-linkedin\" aria-hidden=\"true\"><\/i>\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<div class=\"elementor-share-btn__text\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-share-btn__title\">\n\t\t\t\t\t\t\t\t\t\tLinkedIn\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-22d3810 elementor-widget elementor-widget-related_solutions\" data-id=\"22d3810\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"related_solutions.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"art-solutions-section\"><div class=\"art-section-title\">Discover all of our services and solutions<\/div>    <div class=\"art-solutions\"><div class=\"art-solution\">   <a href=\"https:\/\/www.artea.com\/en\/what-we-do\/\" class=\"art-btn\">What We Do<\/a><\/div>    <\/div> <!-- end art solutions -->\n                      <\/div> <!-- end art solutions section -->\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\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>Convolutional neural networks (CNNs) are a specific type of neural network designed to process data with a grid-like structure, such as images or videos. This architecture has revolutionized the field of computer vision thanks to its ability to recognize complex patterns with extreme accuracy. CNNs are particularly well-suited for image and object recognition, but they [&hellip;]<\/p>\n","protected":false},"author":9,"featured_media":5355,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[87],"tags":[],"class_list":["post-6923","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence-algorithms"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>What Are Convolutional Neural Networks | artea.com<\/title>\n<meta name=\"description\" content=\"Learn what convolutional neural networks (CNNs) are, how they work, and their main applications in the field of artificial intelligence.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.artea.com\/en\/what-are-convolutional-neural-networks\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What Are Convolutional Neural Networks | artea.com\" \/>\n<meta property=\"og:description\" content=\"Learn what convolutional neural networks (CNNs) are, how they work, and their main applications in the field of artificial intelligence.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.artea.com\/en\/what-are-convolutional-neural-networks\/\" \/>\n<meta property=\"og:site_name\" content=\"artea.com | AI for enterprise applications\" \/>\n<meta property=\"article:published_time\" content=\"2024-11-06T15:35:20+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-09-29T07:29:47+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.artea.com\/wp-content\/uploads\/2024\/10\/reti-neurali-scaled.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2560\" \/>\n\t<meta property=\"og:image:height\" content=\"1440\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"artea.com\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"artea.com\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.artea.com\\\/en\\\/what-are-convolutional-neural-networks\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.artea.com\\\/en\\\/what-are-convolutional-neural-networks\\\/\"},\"author\":{\"name\":\"artea.com\",\"@id\":\"https:\\\/\\\/www.artea.com\\\/en\\\/#\\\/schema\\\/person\\\/c518dee823425209ecee41ac7b625051\"},\"headline\":\"WHAT ARE CONVOLUTIONAL NEURAL NETWORKS?\",\"datePublished\":\"2024-11-06T15:35:20+00:00\",\"dateModified\":\"2026-09-29T07:29:47+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.artea.com\\\/en\\\/what-are-convolutional-neural-networks\\\/\"},\"wordCount\":878,\"publisher\":{\"@id\":\"https:\\\/\\\/www.artea.com\\\/en\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/www.artea.com\\\/en\\\/what-are-convolutional-neural-networks\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/www.artea.com\\\/wp-content\\\/uploads\\\/2024\\\/10\\\/reti-neurali-scaled.jpg\",\"articleSection\":[\"Artificial Intelligence &amp; 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