Multimodal AI model combines eye scans for early disease classification
A dual-modality artificial-intelligence model that analyzed both fundus photographs and optical coherence tomography (OCT) scans reported high performance when classifying ...
A dual-modality artificial-intelligence model that analyzed both fundus photographs and optical coherence tomography (OCT) scans reported high performance when classifying ...
A two-season Chinese field study found that fused UAV spectral, texture, LiDAR and temporal features with random forest produced the ...
UAC-Net combined contextual attention and multi-scale feature fusion in a shared neural network that classified three brain-tumor types and delineated ...
An enhanced YOLOv11 model developed for printed circuit board inspection achieved mean average precision of 96.1% at an intersection-over-union threshold ...
A new RGB-depth salient object detection framework combines multi-level attention-based feature fusion with a WebP compression and denoising defense that ...
Researchers have developed a wavelet-transform-based pedestrian detection model that improves accuracy on crowded benchmarks while cutting parameters by nearly 40 ...
A new parallel Transformer-CNN architecture called TCNNISTD achieves state-of-the-art accuracy and real-time speed in detecting infrared targets smaller than ten ...
Researchers at Durham University have developed a dual-stream neural network that applies parallel attention to sensor modalities and time steps, ...
Researchers in India have developed a hierarchical feature fusion transformer that identifies seventeen jute pest species with 98.43 percent accuracy, ...
Researchers in Turkey have built a multimodal Vision Transformer framework that converts Android app features into grayscale and QR code ...
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© 2026 Scienmag - Science Magazine