<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>CNN</title>
	<atom:link href="https://ai-tech.systems/tag/cnn/feed/" rel="self" type="application/rss+xml" />
	<link></link>
	<description>on-device tinyML and AIoT solutions for IoT devices and microcontrollers</description>
	<lastBuildDate>Sun, 31 Aug 2025 21:45:04 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	

<image>
	<url>https://ai-tech.systems/wp-content/uploads/2021/01/cropped-AITS-1-1-32x32.png</url>
	<title>CNN</title>
	<link></link>
	<width>32</width>
	<height>32</height>
</image> 
	<item>
		<title>Keras CIFAR-10 Vision App for Image Classification using Tensorflow</title>
		<link>https://ai-tech.systems/keras-cifar-10-vision-app/</link>
		
		<dc:creator><![CDATA[AITS Admin]]></dc:creator>
		<pubDate>Sun, 11 Dec 2022 14:57:03 +0000</pubDate>
				<category><![CDATA[Blog]]></category>
		<category><![CDATA[CNN]]></category>
		<category><![CDATA[Convolutional Neural Network]]></category>
		<category><![CDATA[embeddedML]]></category>
		<category><![CDATA[Image Classification]]></category>
		<category><![CDATA[Keras CIFAR-10 Vision App]]></category>
		<category><![CDATA[Microcontroller Machine Learning]]></category>
		<category><![CDATA[Tensorflow]]></category>
		<category><![CDATA[tinyML]]></category>
		<guid isPermaLink="false">https://www.ai-tech.systems/keras-cifar-10-vision-app-for-image-classification-using-tensorflow/</guid>

					<description><![CDATA[<p>Photo by Science Magazine on Fiction to Fact In this article, we will focus on building a Convolutional Neural Network (CNN), to recognize and classify images from The CIFAR-10 dataset. The CIFAR-10 dataset is a standard dataset used in computer vision and deep learning community. It consists of 60000 32&#215;32 color images in 10 classes, with [&#8230;]</p>
<p>The post <a href="https://ai-tech.systems/keras-cifar-10-vision-app/">Keras CIFAR-10 Vision App for Image Classification using Tensorflow</a> appeared first on <a href="https://ai-tech.systems">AI Technology &amp; Systems</a>.</p>
]]></description>
		
		
		
			</item>
		<item>
		<title>Hate Speech and Offensive Language Detection</title>
		<link>https://ai-tech.systems/hate-speech-and-offensive-language-detection/</link>
		
		<dc:creator><![CDATA[AITS Admin]]></dc:creator>
		<pubDate>Sat, 10 Dec 2022 13:13:04 +0000</pubDate>
				<category><![CDATA[Use Cases]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[AI for Online Safety]]></category>
		<category><![CDATA[AI Tools for Hate Speech]]></category>
		<category><![CDATA[AI-Tech Systems Hate Speech]]></category>
		<category><![CDATA[Artificial Intelligence Hate Speech]]></category>
		<category><![CDATA[cAInvas]]></category>
		<category><![CDATA[Cainvas Platform]]></category>
		<category><![CDATA[Classification]]></category>
		<category><![CDATA[CNN]]></category>
		<category><![CDATA[CNN Architecture]]></category>
		<category><![CDATA[Content Moderation AI]]></category>
		<category><![CDATA[Convolutional Neural Network]]></category>
		<category><![CDATA[Deep Learning]]></category>
		<category><![CDATA[Deep Learning for Content Moderation]]></category>
		<category><![CDATA[Deep Learning Model]]></category>
		<category><![CDATA[Deep Learning models]]></category>
		<category><![CDATA[DeepC]]></category>
		<category><![CDATA[Detection]]></category>
		<category><![CDATA[Detection model]]></category>
		<category><![CDATA[Digital Civility]]></category>
		<category><![CDATA[embeddedML]]></category>
		<category><![CDATA[Hate Speech and Offensive Language Detection]]></category>
		<category><![CDATA[Hate speech detection]]></category>
		<category><![CDATA[Keras]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[Machine Learning Offensive Language]]></category>
		<category><![CDATA[Microcontroller Machine Learning]]></category>
		<category><![CDATA[Neural Network]]></category>
		<category><![CDATA[Neural Networks]]></category>
		<category><![CDATA[Offensive Language Detection]]></category>
		<category><![CDATA[Online Harassment Prevention]]></category>
		<category><![CDATA[Prediction]]></category>
		<category><![CDATA[tinyML]]></category>
		<category><![CDATA[TinyML Devices]]></category>
		<guid isPermaLink="false">https://www.ai-tech.systems/hate-speech-and-offensive-language-detection/</guid>

					<description><![CDATA[<p>Nowadays we are well aware of the fact that if social media platforms are not handled carefully then they can create chaos in the world. One of the problems faced on these platforms are usage of Hate Speech and Offensive Language. Usage of such Language often results in fights, crimes or sometimes riots at worst. [&#8230;]</p>
<p>The post <a href="https://ai-tech.systems/hate-speech-and-offensive-language-detection/">Hate Speech and Offensive Language Detection</a> appeared first on <a href="https://ai-tech.systems">AI Technology &amp; Systems</a>.</p>
]]></description>
		
		
		
			</item>
		<item>
		<title>Arrhythmia prediction on ECG data using CNN</title>
		<link>https://ai-tech.systems/arrhythmia-prediction-on-ecg-data-using-cnn/</link>
		
		<dc:creator><![CDATA[AITS Admin]]></dc:creator>
		<pubDate>Fri, 09 Dec 2022 10:44:59 +0000</pubDate>
				<category><![CDATA[Blog]]></category>
		<category><![CDATA[Arrhythmia prediction]]></category>
		<category><![CDATA[Arrhythmia prediction on ECG data]]></category>
		<category><![CDATA[classify heartbeats]]></category>
		<category><![CDATA[CNN]]></category>
		<category><![CDATA[Deep Learning]]></category>
		<category><![CDATA[ECG Data]]></category>
		<category><![CDATA[embeddedML]]></category>
		<category><![CDATA[Microcontroller Machine Learning]]></category>
		<category><![CDATA[tinyML]]></category>
		<guid isPermaLink="false">https://www.ai-tech.systems/arrhythmia-prediction-on-ecg-data-using-cnn/</guid>

					<description><![CDATA[<p>Using convolutional neural networks to classify heartbeat sounds into five categories. Photo by Chan Luu on Behance, Adobe Arrhythmia refers to an irregularity in the rate or rhythm of the heartbeat. This includes beating too fast or too slow or with an irregular rhythm. Deep learning models have proven useful and very efficient in the medical [&#8230;]</p>
<p>The post <a href="https://ai-tech.systems/arrhythmia-prediction-on-ecg-data-using-cnn/">Arrhythmia prediction on ECG data using CNN</a> appeared first on <a href="https://ai-tech.systems">AI Technology &amp; Systems</a>.</p>
]]></description>
		
		
		
			</item>
		<item>
		<title>Captcha recognition — on cAInvas</title>
		<link>https://ai-tech.systems/captcha-recognition-on-cainvas/</link>
		
		<dc:creator><![CDATA[AITS Admin]]></dc:creator>
		<pubDate>Thu, 08 Dec 2022 16:11:07 +0000</pubDate>
				<category><![CDATA[Blog]]></category>
		<category><![CDATA[cAInvas]]></category>
		<category><![CDATA[Captcha recognition]]></category>
		<category><![CDATA[CNN]]></category>
		<category><![CDATA[embeddedML]]></category>
		<category><![CDATA[Microcontroller Machine Learning]]></category>
		<category><![CDATA[tinyML]]></category>
		<guid isPermaLink="false">https://www.ai-tech.systems/captcha-recognition-on-cainvas/</guid>

					<description><![CDATA[<p>Transcribe captcha images to text using convolutional neural networks. Photo by Alex Castro CAPTCHA stands for Completely Automated Public Turing Test. It is a type of challenge-response test to determine whether the user is a human or an automated system in the computing world. The earliest form of CAPTCHA involved recognizing a sequence of letters or [&#8230;]</p>
<p>The post <a href="https://ai-tech.systems/captcha-recognition-on-cainvas/">Captcha recognition — on cAInvas</a> appeared first on <a href="https://ai-tech.systems">AI Technology &amp; Systems</a>.</p>
]]></description>
		
		
		
			</item>
		<item>
		<title>Object Classifier Using CNN</title>
		<link>https://ai-tech.systems/object-classifier-using-cnn/</link>
		
		<dc:creator><![CDATA[AITS Admin]]></dc:creator>
		<pubDate>Sat, 03 Dec 2022 18:39:16 +0000</pubDate>
				<category><![CDATA[Blog]]></category>
		<category><![CDATA[CNN]]></category>
		<category><![CDATA[embeddedML]]></category>
		<category><![CDATA[Microcontroller Machine Learning]]></category>
		<category><![CDATA[Object Classifier]]></category>
		<category><![CDATA[Object Classifier Using CNN]]></category>
		<category><![CDATA[tinyML]]></category>
		<guid isPermaLink="false">https://www.ai-tech.systems/object-classifier-using-cnn/</guid>

					<description><![CDATA[<p>Photo by Cabify Design on Dribbble According to Wikipedia: Contextual image classification, a topic of pattern recognition in computer vision, is an approach of classification based on contextual information in images. “Contextual” means this approach is focusing on the relationship of the nearby pixels, which is also called neighborhood. The goal of this approach is to [&#8230;]</p>
<p>The post <a href="https://ai-tech.systems/object-classifier-using-cnn/">Object Classifier Using CNN</a> appeared first on <a href="https://ai-tech.systems">AI Technology &amp; Systems</a>.</p>
]]></description>
		
		
		
			</item>
		<item>
		<title>Malaria Parasite Detection using a Convolutional Neural Network on the Cainvas Platform</title>
		<link>https://ai-tech.systems/malaria-parasite-detection-using-a-convolutional-neural-network-on-the-cainvas-platform/</link>
		
		<dc:creator><![CDATA[AITS Admin]]></dc:creator>
		<pubDate>Fri, 02 Dec 2022 16:10:31 +0000</pubDate>
				<category><![CDATA[Blog]]></category>
		<category><![CDATA[Cainvas Platform]]></category>
		<category><![CDATA[CNN]]></category>
		<category><![CDATA[Convolutional Neural Network]]></category>
		<category><![CDATA[embeddedML]]></category>
		<category><![CDATA[Malaria Parasite Detection]]></category>
		<category><![CDATA[Microcontroller Machine Learning]]></category>
		<category><![CDATA[tinyML]]></category>
		<guid isPermaLink="false">https://www.ai-tech.systems/malaria-parasite-detection-using-a-convolutional-neural-network-on-the-cainvas-platform/</guid>

					<description><![CDATA[<p>Photo by Kurzgesagt — In a Nutshell on YouTube Introduction Malaria is a life-threatening disease caused by parasites that are transmitted to people through the bites of infected female Anopheles mosquitoes. The World Health Organization states the following daunting facts about the disease on its website: In 2019, there were an estimated 229 million cases of malaria worldwide. [&#8230;]</p>
<p>The post <a href="https://ai-tech.systems/malaria-parasite-detection-using-a-convolutional-neural-network-on-the-cainvas-platform/">Malaria Parasite Detection using a Convolutional Neural Network on the Cainvas Platform</a> appeared first on <a href="https://ai-tech.systems">AI Technology &amp; Systems</a>.</p>
]]></description>
		
		
		
			</item>
		<item>
		<title>FISH BREED CLASSIFICATION</title>
		<link>https://ai-tech.systems/fish-breed-classification/</link>
		
		<dc:creator><![CDATA[AITS Admin]]></dc:creator>
		<pubDate>Fri, 02 Dec 2022 13:58:36 +0000</pubDate>
				<category><![CDATA[Use Cases]]></category>
		<category><![CDATA[Classification]]></category>
		<category><![CDATA[CNN]]></category>
		<category><![CDATA[embeddedML]]></category>
		<category><![CDATA[Fish Breed]]></category>
		<category><![CDATA[Fish Breed Classfication]]></category>
		<category><![CDATA[Kernel Link]]></category>
		<category><![CDATA[Microcontroller Machine Learning]]></category>
		<category><![CDATA[tinyML]]></category>
		<guid isPermaLink="false">https://www.ai-tech.systems/fish-breed-classification/</guid>

					<description><![CDATA[<p>Photo by July PJuxa (Puchkova) on Dribbble Fishes also known as Ichthyology, accounts for the majority of Sea Life on our planet. They range from small centimetre to many meters. It can be even said that is one of the most diversified species on the planet that we mere humans have not explored. Distinguishing them is [&#8230;]</p>
<p>The post <a href="https://ai-tech.systems/fish-breed-classification/">FISH BREED CLASSIFICATION</a> appeared first on <a href="https://ai-tech.systems">AI Technology &amp; Systems</a>.</p>
]]></description>
		
		
		
			</item>
		<item>
		<title>Spider Breed Classification with Cainvas</title>
		<link>https://ai-tech.systems/spider-breed-classification-with-cainvas/</link>
		
		<dc:creator><![CDATA[AITS Admin]]></dc:creator>
		<pubDate>Thu, 01 Dec 2022 16:25:14 +0000</pubDate>
				<category><![CDATA[Blog]]></category>
		<category><![CDATA[cAInvas]]></category>
		<category><![CDATA[Classification]]></category>
		<category><![CDATA[CNN]]></category>
		<category><![CDATA[embeddedML]]></category>
		<category><![CDATA[Microcontroller Machine Learning]]></category>
		<category><![CDATA[Prediction]]></category>
		<category><![CDATA[Spider Breed]]></category>
		<category><![CDATA[Spider Breed Classification with Cainvas]]></category>
		<category><![CDATA[tinyML]]></category>
		<guid isPermaLink="false">https://www.ai-tech.systems/spider-breed-classification-with-cainvas/</guid>

					<description><![CDATA[<p>Photo by MinooIravani on Dribbble Spiders also known as Araneae Scientifically have more than 43000 breed. That is really a lot compared to dogs 250, cats 70. Although one doesn’t have a daily encounter with them they are a really interesting species. Spiders can apparently fish, spider’s web weight to strength ratio even surpasses steel and [&#8230;]</p>
<p>The post <a href="https://ai-tech.systems/spider-breed-classification-with-cainvas/">Spider Breed Classification with Cainvas</a> appeared first on <a href="https://ai-tech.systems">AI Technology &amp; Systems</a>.</p>
]]></description>
		
		
		
			</item>
	</channel>
</rss>
