Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to the MNIST digits dataset. The "Hello World" of image ...

They are developing a Quantum Convolutional Neural Network (QCNN) architecture to enhance the performance of traditional computer vision tasks using quantum mechanics principles. The Quantum ...

Meanwhile, the existing convolutional neural networks (CNNs) have the problem of low fault recognition rates. This paper proposes a novel convolutional neural network with one-dimensional structure ...

Applying convolutional neural networks to image enhancement has obvious advantages and can solve challenges in different environments. The essence of CNN is to map the input image to a new ...

This article is published by AllBusiness.com, a partner of TIME. A Convolutional Neural Network (CNN) represents a sophisticated advancement in artificial intelligence technology, specifically ...

A subsequent article, “Training convolutional neural networks” discusses how CNN models are trained. Part 3 will examine a specific use case to test the model using a dedicated AI microcontroller.

we use ML for improvement of video compression through simple ML forms as decision trees to more advanced deep Convolutional Neural Networks (CNNs). CNNs are particularly effective at solving ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...