Agricultural engineers developed a dual-stream neural network combining self-supervised visual learning, asymmetric attention, and daily consistency loss to estimate finishing ...
A geometry-first computer vision framework that decouples three-dimensional surface reconstruction from two-dimensional mask supervision reduced maize kernel counting errors to ...
Agricultural engineers have developed an automated computer vision framework that estimates piglet body weight from standard overhead video feeds by ...
Agricultural engineers developed a multi-task computer vision framework combining depth-assisted foundation model annotation with an enhanced Mask2Former network to evaluate ...
A comprehensive systematic review of literature from 2018 to 2025 reveals that while deep learning achieves high benchmark accuracy for ...
A systematic review of 62 studies reveals that deep learning models effectively monitor marine biodiversity across distinct aquatic mediums despite ...
Researchers combined YOLOv8 object detection with the Segment Anything Model to identify urban rooftops from satellite imagery and estimate solar ...
A hybrid deep learning framework combining lightweight super-resolution, transformer-based masked attention, and density regression significantly improves platelet detection and counting ...
Agricultural engineering researchers have developed a lightweight deep learning model capable of segmenting citrus flowers and young fruitlets in real ...
An open-source AI workflow now extracts seismic behaviour modifiers such as block position, direction and plan irregularity directly from digitised ...
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