Predicting tropical cyclones (TCs) accurately is crucial for disaster mitigation and public safety. Although the forecasting accuracy of TC tracks has improved substantially in recent decades, ...

Abstract: In this study, we studied unsupervised multiview learning techniques focused on maximizing correlation, particularly Deep Canonically Correlated Autoencoders (DCCAE). The goal of this study ...

Over the past decade, deep learning (DL) techniques such as convolutional neural networks (CNNs) and long short-term memory (LSTM) networks have played a pivotal role in advancing the field of ...

Deep learning is an AI function and a subset of machine learning, used for processing large amounts of complex data. Deep learning can automatically create algorithms based on data patterns.

Royalty-free licenses let you pay once to use copyrighted images and video clips in personal and commercial projects on an ongoing basis without requiring additional payments each time you use that ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...

I'm diving deep into the intersection of infrastructure and machine learning. I'm fascinated by exploring scalable architectures, MLOps, and the latest advancements in AI-driven systems ...

Abstract: Convolutional Neural Networks (CNNs) have shown remarkable success across numerous tasks such as image classification, yet the theoretical understanding of their convergence remains ...

1 Department of Nuclear Medicine, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, China 2 Department of Nuclear Medicine, Meizhou People’s Hosptal (Meizhou ...

ABSTRACT: In the context of the rapid development of intelligent manufacturing, the stable operation of mechanical equipment is crucial for maintaining industrial production continuity and achieving ...