Researchers have developed a geometric deep learning approach to uncover shared brain activity patterns across individuals.

A new international and multidisciplinary study has unveiled a novel framework for understanding the concept of time ...

The efficiency of wireless charging systems is limited by power loss occurring due to frequency changes in the resonant circuits that enable power transfer. These necessary modulations reduce ...

This is a comprehensive protocol for the analysis of white matter diffusion-weighted magnetic resonance imaging data, which enables the representation of neuroanatomical atlases by using network ...

We're ranked 11th in the world and third in the UK for Architecture (QS World University Rankings by Subject 2021). Shape the future of the built environment by exploring new, heritage-friendly and ...

Nuclear magnetic resonance (NMR) spectroscopy is a technique that detects the chemical environment of atomic nuclei by the absorption of radio-frequency electromagnetic radiation when in the ...

To tackle such a problem, we propose a novel method, namely the Cascaded Adaptive Network (i.e., CA-Net), to comprehensively enhance the quality of underwater images. Specifically, our network adopts ...

To alleviate this concern, we propose a network based on spatial-temporal interaction and frequency adaptive awareness (SIFANet). The network contains three main modules. Specifically, we design a ...

The project is built with PyTorch 3.8, PyTorch 1.8.1. CUDA 10.2, cuDNN 7.6.5 For installing, follow these instructions: conda install pytorch=1.8.1 torchvision=0.9.1 -c pytorch pip install tensorboard ...

After hours: February 14 at 6:30:25 PM EST Loading Chart for EXTR ...

A deep learning model and training/testing/inference library in PyTorch for segmentation, classification, object detection and self-supervised learning using radiology data.