eLife

“What” × “When” working memory representations using Laplace Neural Manifolds

The results include a comparison between two different basis functions for temporal selectivity and how these generate different predictions for the dynamics of neural populations. The conclusions are ...

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 ...
The Next Platform

Dassault And Nvidia Bring Industrial World Models To Physical AI

During his more than two decades with Nvidia, Rev Lebaredian has had a ringside seat to the show that has been the evolution ...
Scientific Research Publishing

Research on Structural Damage Identification Method Based on Convolutional Neural Network ()

1 College of Finance and Commerce, Guangzhou Railway Polytechnic, Guangzhou, China. 2 School of Intelligent Construction and Civil Engineering, Zhongyuan University of Technology, Zhengzhou, China. 3 ...
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 ...
Frontiers

Quantized convolutional neural networks: a hardware perspective

With the rapid development of machine learning, Deep Neural Network (DNN) exhibits superior performance in solving complex problems like computer vision and natural language processing compared with ...
IEEE

Introduction to Heterogeneous Knowledge Transfer for Quantum Convolutional Neural Networks

Abstract: The convolutional neural network (CNN) is widely utilized in computer vision due to its ability to effectively harness correlation information within data. However, when the data's ...
Scientific Research Publishing

Speech Emotion Recognition Based on CNN-Transformer with Different Loss Function ()

Speech Emotion Recognition (SER) is crucial for enhancing human-computer interactions by enabling machines to understand and respond appropriately to human emotions. However, accurately recognizing ...