For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...
WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification BEIJING, Jan. 15, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global ...
A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...
One of the most difficult challenges in payment card fraud detection is extreme class imbalance. Fraudulent transactions ...
The neural network approach uses multiple or “deep” layers that learn to identify increasingly complex features in data. The ...
Evolving challenges and strategies in AI/ML model deployment and hardware optimization have a big impact on NPU architectures ...
“We must strive for better,” said IBM Research chief scientist Ruchir Puri at a conference on AI acceleration organised by the computer company and the IEEE in November. He expects almost all language ...
Intrusion detection systems, long constrained by high false-positive rates and limited adaptability, are being re-engineered ...
Why is a Chinese quant shop behind one of the world’s strongest open-weight LLMs? It turns out that modern quantitative ...
The 2026 International Production & Processing Expo (IPPE) is about to open its doors, and Shanghai Xiashu Intelligent ...
Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving ...
Monitoring forest health typically relies on remote sensing tools such as light detection and ranging (LiDAR), radar, and multispectral photography. While radar and LiDAR penetrate canopies to reveal ...
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