Researchers at Soongsil University (Korea) published “A Survey on Efficient Convolutional Neural Networks and Hardware Acceleration.” Abstract: “Over the past decade, deep-learning-based ...

In this article, we delve into the fundamentals of Convolutional Neural Networks, their architecture, and their impact on the world of computer vision.

This article will provide an overview of the most common neural network architectures -- including recurrent neural networks and convolutional neural -- and how they can be implemented to aid ...

Convolutional neural networks One of the key components of most deep learning–based computer vision applications is the convolutional neural network (CNN).

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.

A new technical paper titled “Optimizing event-based neural networks on digital neuromorphic architecture: a comprehensive design space exploration” was published by imec, TU Delft and University of ...

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

Convolutional Neural Networks for MNIST Data Using PyTorch Dr. James McCaffrey of Microsoft Research details the "Hello World" of image classification: a convolutional neural network (CNN) applied to ...