Semiconductor Engineering

Convolutional Neural Networks: Co-Design of Hardware Architecture and Compression Algorithm

“Over the past decade, deep-learning-based representations have demonstrated remarkable performance in academia and industry. The learning capability of convolutional neural networks (CNNs) originates ...
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 ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
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 ...
Semiconductor Engineering

Convolutional Neural Network With INT4 Optimization

INT8 provides better performance with comparable precision than floating point for AI inference. But when INT8 is unable to meet the desired performance with limited resources, INT4 optimization is ...
InfoQ

Meta AI’s Convolution Networks Upgrade Improves Image Classification

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...

WiMi Studies Hybrid Quantum-Classical Inception Neural Network Model for Image Classification

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) (WiMi or the Company), a leading global Hologram Augmented Reality (AR) Technology ...
pv magazine International

PV module fault diagnosis uses convolutional neural network

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...