In the cerebral cortex, numerous neurons exchange information through junctions known as synapses. The strength of each ...

Unlock the blueprint for future-proof data center networks in the AI era. This Nokia whitepaper offers essential insights on ...

This important study demonstrates the significance of incorporating biological constraints in training neural networks to develop models that make accurate predictions under novel conditions. By ...

Disease Diagnosis in early stages is crucial in today's world. Big data has been a boon in the medical and health care industry. There have been various advancements in machine learning algorithms ...

This repository is the open source code for my latest work: "Through-the-Wall Radar Human Activity Recognition WITHOUT Using Neural Networks", submitted to arXiv. Fig. 1. Current works in this field ...

Many deep learning-based methods have been developed to improve the performance of 6mA site prediction. In this study, to further improve the performance of 6mA site prediction, we propose a new meta ...

Data-driven deep learning techniques have made notable advancements in modeling electromagnetic scattering problems. However, its accuracy on the testing dataset can be heavily reduced when data ...

Physically based models for spatial flood prediction are time and computationally expensive. Data-driven models, while faster, require large amounts of data for adjustment. This study presents an ...