Researchers developed a convolutional neural network named RegFractNet that quantifies Hurst exponents and fractal dimensions of urban terrain from satellite ...
A simulated hybrid quantum-classical neural network utilizing an optimized gate configuration achieved high accuracy in identifying synthetic speech on a ...
Researchers have introduced AgarwoodNet, a lightweight convolutional neural network that classified 14 categories of agarwood leaf conditions with 96.66 percent ...
Combining Raman scattering and autofluorescence signals with machine learning allows portable spectrometers to reliably differentiate newly harvested green tea from ...
Researchers have developed an online physics-informed transformer that estimates lithium-ion battery health using only a one-minute relaxation voltage segment.
A deep learning framework predicts transverse stress evolution and Young's modulus in synthetic hemp fibers in under one second per ...
A terahertz time-domain spectroscopy and artificial intelligence system identified five common meat species with 98.3 percent accuracy and quantified adulteration ...
A new hybrid deep learning framework combining convolutional networks and transformers improves automated identification of overlapping cassava leaf diseases under ...
A deep learning framework that decodes spatial intratumor heterogeneity from preoperative computed tomography scans predicts cervical lymph node metastasis and ...
A fine-grained football action recognition model combining spatio-temporal compression sequences and multi-head cross-attention surpassed existing methods on the SoccerNet-v2 benchmark ...
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