AI Learns to Read Pear Leaves: Hybrid Network Spots Disease With 92.69% Accuracy
A dual-track deep learning network combining Swin Transformer global context with convolutional feature pyramids classifies pear leaf diseases with 92.69% ...
A dual-track deep learning network combining Swin Transformer global context with convolutional feature pyramids classifies pear leaf diseases with 92.69% ...
Emotions leave fingerprints in the brain that are far more honest than a smile. A team of researchers in China ...
Ghent University researchers introduce culture networks, a psychometric network method that maps organizational culture as a web of interconnected elements, ...
A sweeping integrative review argues that major depressive disorder arises from interacting molecular dysregulation and large-scale brain network dysfunction, while ...
The shift from viewing dystonia as a localized circuit defect to understanding it as a distributed network disorder has profound ...
A hybrid model pairing a ConvNeXt backbone with a Kolmogorov–Arnold Network head reaches 94.5 percent accuracy in four-way Alzheimer's staging ...
A longitudinal fMRI study of 115 adolescents with externalizing disorders shows that reward network activation during risky decision-making predicts problematic ...
Deep beneath our feet, in the thin layer of soil, rock, water, and air that scientists call the Critical Zone, ...
A deep learning model small enough to fit in roughly three megabytes of memory has been trained to spot epileptic ...
A mathematical model of 10 interacting nephrons reveals that all operate in weakly chaotic states, with electrical signaling through the ...
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© 2025 Scienmag - Science Magazine