AI Facial Landmarks Enable Non-Invasive Fatigue Assessment in Working Dogs
Researchers developed a non-invasive, video-only framework using 46 anatomically grounded facial landmarks to automate fatigue assessment in working dogs.
Researchers developed a non-invasive, video-only framework using 46 anatomically grounded facial landmarks to automate fatigue assessment in working dogs.
Researchers at the University of Rochester and NVIDIA developed PixelDiT2, a pixel-space diffusion model that nearly matches state-of-the-art image generators ...
Researchers report a lightweight detection model that improves small-drone recognition in complex backgrounds while sustaining real-time speeds on edge hardware.
A new study from Bahawalpur, Pakistan, finds that transformer models, led by the Swin Transformer, classify cotton leaf diseases more ...
A hybrid ResNet50 and Transformer model achieved 89.7 percent accuracy on the FER2013 facial emotion benchmark, with an ablation study ...
A new review describes how AI-based imaging and sensing technologies can detect packaging film defects that traditional meat inspection methods ...
A deep learning framework trained on orthophotos from the 2011 Great East Japan Earthquake detected damaged roads and bridges with ...
A CNN running on a host PC with Arduino-based servo actuation predicted steering angles with a validation MAE of 0.093 ...
Researchers used diffusion models to generate weather- and lighting-altered training videos with intact annotations, improving cross-dataset foreground segmentation from 0.76 ...
A geological-feature enhanced Cascade Mask R-CNN suppresses spectral confusion and class imbalance to recognize landslides in high-resolution satellite imagery, cutting ...
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© 2025 Scienmag - Science Magazine