AI Network Learns to Spot Faint Damage on Ancient Murals
Researchers have developed MuHP-DLNet, a multi-stage deep learning network with a damage-aware dynamic loss that improves the detection and segmentation ...
Researchers have developed MuHP-DLNet, a multi-stage deep learning network with a damage-aware dynamic loss that improves the detection and segmentation ...
Researchers have built a transformer-based intrusion detection framework that models relationships among network traffic features and outperforms nine baseline AI ...
A new hybrid deep learning model tuned by a snake-inspired optimization algorithm achieves 98.13 percent accuracy in classifying sentiment from ...
Researchers in China have built a deep-learning model that fuses CT, MRI, and 3D radiation dose data to predict which ...
Researchers built an expert-annotated Chinese knee MRI dataset and an optimized Swin-Unet Transformer model that segments femoral and tibial cartilage ...
A new AI framework called RCTE improves the detection of small lesions and complex dental structures in panoramic radiographs while ...
Researchers at Harbin Normal University have developed WFGformer, a dual-branch transformer network that uses Haar wavelet frequency decomposition to restore ...
A Transformer-based multimodal AI model can predict the flavor profile and macronutrient content of ready-to-eat meals directly from product images, ...
Researchers at Tsinghua University have developed a Series Saliency module guided by large language models that improves the accuracy and ...
Researchers have developed a transformer-based framework with local-global attention that identifies writers from scanned handwriting without reading the text, achieving ...
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© 2026 Scienmag - Science Magazine