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Photonic AI chip targets faster convolutions with far less energy

Engineers at the University of Florida have built a photonic chip that performs convolutions, the most compute-heavy operation in modern AI, using light instead of electricity and delivering roughly ...
Frontiers

Toward a Visualized Classifier for Depression: Characterization of Hemodynamic Patterns Using Time-Domain fNIRS

The final, formatted version of the article will be published soon. Background: Major depressive disorder (MDD) is a chronic illness associated with considerable morbidity and is characterized by high ...
IEEE

RRAM-Based Spectral-Domain Convolution Accelerator for Reliable and Energy-Efficient CNN Inference

Abstract: The growing computational demands of convolutional neural networks (CNNs) have motivated the use of spectral-domain inference as an alternative to costly spatial-domain convolutions. In this ...
IEEE

Sequential Inversion for Helicopter Time-Domain Electromagnetics Based on a Regularized Extended Kalman Filtering

Abstract: The helicopter time-domain electromagnetic method (HTEM) has been widely applied in challenging geological terrains, particularly in large-scale mineral exploration, underground water ...