What is CNN in Deep Learning? The AI Behind Computer Vision

Learn what CNN is in deep learning, how they work, and why they power modern image recognition AI and computer vision ...
Embedded

Understanding convolutional neural networks

The world of artificial intelligence (AI) is rapidly evolving, and AI is increasingly enabling applications that were previously unattainable or very difficult to implement. A subsequent article, ...
Techno-Science.net on MSN

AI: Some architectures are fundamentally close to the human brain

Some artificial intelligence models can already resemble the human brain even before having learned anything. This surprising ...
Tech Xplore on MSN

Small changes make some AI systems more brain-like than others

Artificial intelligence systems that are designed with a biologically inspired architecture can simulate human brain activity ...
Electronic Design

Improving Convolutional Neural Networks at the Edge

The AI revolution continuously requires new tools and methods to take full advantage of its promise, especially when dealing with imaging data beyond visible wavelengths of the electromagnetic ...
Visual Studio Magazine

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 the MNIST digits dataset. The "Hello World" of image ...
InfoWorld

The most popular neural network styles and how they work

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 ...
The Next Web

Deep learning models DON’T need to be black boxes — here’s how

Deep neural networks can perform wonderful feats thanks to their extremely large and complicated web of parameters. But their complexity is also their curse: The inner workings of neural networks are ...
TMCnet

WiMi Studies Hybrid Quantum-Classical Learning Architecture for Multi-Class Image Classification

In this architecture, the training process adopts a joint optimization mechanism based on classical cross-entropy loss. WiMi treats the measurement probability distribution output by the quantum ...