Information collected during the yearslong Salt Typhoon attack could allow Beijing’s intelligence services to track targets from the United States and dozens of other countries. By Adam Goldman ...

Objective: The aim of the present study proposed a deep learning framework for different influenza epidemic states based on Baidu index and the influenza-like-illness rate (ILI%). Methods: Official ...

Abstract: This research addresses the challenge of camera calibration and distortion parameter prediction from a single image using deep learning models. The main contributions of this work are: (1) ...

Introduction: Recent advances in artificial intelligence have transformed the way we analyze complex environmental data. However, high-dimensionality, spatiotemporal variability, and heterogeneous ...

This a project of Stock Market Analysis And Forecasting Using Deep Learning(pytorch,gru). A stock market, equity market, or share market is the aggregation of buyers and sellers of stocks (also called ...

Deep learning (DL) is a type of artificial intelligence (AI) that utilizes artificial neural networks (ANNs) to process data through two or more layers, each of which can recognize complex features of ...

Objective: This study aims to develop a multimodal deep learning-based stress detection method (MMFD-SD) using intermittently collected physiological signals from wearable devices, including ...

Abstract: This study explores the application of deep learning models combined with SHAP (SHapley Additive exPlanations) for breast cancer classification using gene expression data. Our model ...

This review focuses on the recent advancements in neuroimaging enabled by deep learning techniques, specifically highlighting their applications in brain disorder detection and diagnosis. The ...