AI Learns to Map Crops From Image Labels Alone, Five Times Faster
Researchers have unveiled a weakly supervised AI framework that segments crops, weeds and soil from image-level labels alone, achieving 76.04 ...
Researchers have unveiled a weakly supervised AI framework that segments crops, weeds and soil from image-level labels alone, achieving 76.04 ...
Researchers developed RIDGE, a weakly supervised deep learning system that predicts gene expression signatures and biomarkers such as microsatellite instability ...
Researchers have developed a bidirectional conditional diffusion network that simulates and reconstructs photomultiplier tube waveforms with near-supervised accuracy using only ...
Researchers have introduced PMGL-GAD, a framework that combines training-free green learning features with a global attention disambiguation module to solve ...
Researchers have developed a focused positive-unlabeled learning method that uses focal loss to achieve state-of-the-art performance on severely imbalanced datasets ...
Researchers have developed CROWN, a self-supervised visual foundation model pretrained on more than ten million cytology images that achieved top ...
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© 2025 Scienmag - Science Magazine