This valuable study introduces a self-supervised machine learning method to classify C. elegans postures and behaviors directly from video data, offering an alternative to the skeleton-based ...

Turing Award recipients Richard Sutton and Andrew Barto believe reinforcement learning will play a role in artificial general ...

Tulasi Naga Subhash Polineni’s research offers a timely solution that can serve as a blueprint for the next generation of public health infrastructure.

The European Commission published guidelines that clarify the definition of AI systems under the AI Act, analyzing each component of the definition ...

Abstract: This study introduces a novel representation learning method to enhance unsupervised deep clustering in Human Activity Recognition (HAR). Traditional unsupervised deep clustering methods ...

The self-supervised learning AI tool is designed to process vast data sets to provide insights into climate and environmental ...

Module 1: Customer Segmentation We examine how supervised and unsupervised learning methods help identify meaningful customer segments, enabling more effective targeting and engagement strategies.

The Deep Learning Market, valued at approximately USD 37.15 billion in 2021, is poised for remarkable growth over the forecast period of 2022-2029. With a projected healthy growth rate exceeding 33.5% ...

Most existing methods employ machine learning-based methods to ... challenges when handling multiple complex lesions. This paper proposes an unsupervised correlation learning-based clustering model ...

Tariff evasion is the new money laundering. As global commerce evolves, this emerging reality poses a critical concern for ...