A team at the University of California, San Diego has redesigned how RRAM operates in an effort to accelerate the execution ...

The research, titled AI-Driven Hybrid Deep Learning and Swarm Intelligence for Predictive Maintenance of Smart Manufacturing Robots in Industry 4.0 and published in Electronics, introduces an AI ...

Edge AI addresses high-performance, low-latency requirements by embedding intelligence directly into industrial devices.

This project explores the application of recursive neural networks (RNNs) in natural language processing, specifically for part-of-speech (POS) tagging. Drawing on foundational work by Socher et al.

1 Exploration and Development Research Institute of Sinopec Shengli Oil Field Company, Dongying, Shandong, China 2 School of Petroleum Engineering, China University of Petroleum (East China), Qingdao, ...

Introduction: As the number of Internet of Things (IoT) devices grows quickly, cyber threats are becoming more complex and increasingly sophisticated; thus, we need a more robust network security ...

Abstract: The paper treats an issue of the neural networks application for solving various energy supply difficulties having become more urgent with the years to come. The neural networks of various ...

Summary: Decision-making often involves trial and error, but conventional models assume we always act optimally based on past experience. A new study used small, interpretable artificial neural ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...