BioCompNet: a dual-channel deep learning framework for automated body composition analysis from fat-water MRI sequences. (A) Schematic of the dual-channel 2-dimensional (2D) U-Net architecture used to ...
The echocardiography in PAH deep learning workflow demonstrated good accuracy and acceptable precision for peak TRV, RV basal diameter, TAPSE, and RA area. A fully automated deep learning (DL) ...
Altman taps a leading researcher for his brain-computer interface startup, suggesting a much less invasive approach than Elon Musk’s Neuralink. Altman taps a leading researcher for his brain-computer ...
Abstract: The use of deep learning for sound event localization and classification with Wireless Acoustic Sensor Networks (WASNs) is an emerging research area. However, current methods for sound event ...
Introduction: Alzheimer’s disease (AD) is one of the most common neurodegenerative disabilities that often leads to memory loss, confusion, difficulty in language and trouble with motor coordination.
Abstract: Historical satellite imagery lacks efficient methods for automated land use mapping, particularly when working with CORONA satellite data from the Cold War era. These high-resolution images ...
Researchers have developed a deep learning model called LSTM-SAM that predicts extreme water levels from tropical cyclones more efficiently and accurately, especially in data-scarce coastal regions, ...
A metamaterial is a composite material that exhibits unique properties due to its structure, and now researchers have used one featuring a small sawtooth pattern on its surface to move and position ...
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