Broad Learning Systems (BLS) have emerged as a promising alternative to conventional deep learning architectures by utilising random feature mapping and incremental learning paradigms that expand ...

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 ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

Bridging speed and accuracy in radiation therapy QA Led by Professor Fu Jin, the study addresses a critical challenge in ...

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

Nextchip license NeuPro-M NPU to bring powerful and highly efficient AI capabilities to boost performance and capabilities of automotive safety systems ROCKVILLE, Md., April 22, 2025 /PRNewswire/ -- ...

Future Market Insights (FMI) projects the Neural Processors Market to grow from USD 176 million in 2025 to USD 1,010 million by 2035, advancing at a 19.1% CAGR. This surge is being driven by the ...

Deep learning is rapidly becoming an indispensable element in machine vision solutions. Its application is proving to be particularly useful for identifying objects and features in images. Deep ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...