Coordinating complicated interactive systems, whether it's the different modes of transportation in a city or the various ...

This study addresses the growing demand for news text classification driven by the rapid expansion of internet information by proposing a classification algorithm based on a Bidirectional Gated ...

The rapid growth of mobile computing, AI, and Automotive technologies is driving demand for faster, more efficient, and ...

A shocking upset on The Masked Singer after the "Lucky Six" came together for the first time all season to blow everyone away ...

Abstract: This article presents a deep-learning ... Class F power amplifiers (PAs). We use convolutional neural networks (CNNs) to predict the scattering parameters of pixelated electromagnetic (EM) ...

This study introduces enhanced deep learning architectures, Residual-based Attention Model and Inverted Residual-based Attention Model, combined with explainable AI techniques to improve the ...

They all basically work in the same way: a model containing billions of parameters is deep-trained on huge datasets made up ... who runs EPFL's Theory of Machine Learning Laboratory. "A hefty chunk of ...

The big challenge in deep learning is that you need a lot of data to train the neural network. Fortunately, one of my ...