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Deep learning detects foodborne bacteria within three hours by eliminating debris misclassifications
Researchers have significantly enhanced an artificial intelligence tool used to rapidly detect bacterial contamination in food by eliminating misclassifications of food debris that looks like bacteria ...
Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.
Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...
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Detection of concealed explosives using terahertz spectral imaging and deep learning
Detecting concealed explosives and chemical threats constitutes a critical challenge in global security, yet current technologies often face significant operational limitations. While X-ray scanners ...
This study established a cascade model by integrating deep learning-driven classifiers and GDL models, identified tetrahydrocarbazole derivatives with subnanomolar activity against pan-cancer cells ...
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