A site called ``Animated AI'' has been published that uses animation to explain ``convolutional neural networks (CNN)'', which are widely used in the field of machine learning. Actions that are ...

Convolutional Neural Networks (CNN) are mainly used for image recognition. The fact that the input is assumed to be an image enables an architecture to be created such that certain properties can be ...

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 ...

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 ...

Although machine learning is becoming more popular in different fields of Earth Sciences, some concepts of convolutional neural networks may be vaguely understood by non-practitioners. In this ...

However, in some resource-limited, high-performance and low-latency scenarios (such as the resource-power-sensitive edge side and low-latency ADAS scenario), low bit quantization of neural networks is ...

We present a method for conditional time series forecasting based on an adaptation of the recent deep convolutional WaveNet architecture. The proposed network contains stacks of dilated convolutions ...

A Convolutional Neural Network (CNN) is a form of artificial intelligence that plays a key role in the AI ecosytem due to its ability to analyze and understand visual data. The need to decipher ...

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.