Abstract: This research outlines the significance of semi-supervised machine learning (SSML) in dealing with the intricate characteristics of electrical machines. SSML provides a key benefit in ...

The Indian Institute of Science has announced an online course on machine learning for 6G wireless communication under its ...

An algorithm that finds lost civilizations is helping archaeologists use AI to predict where ancient sites may still be hidden.

Shallem, Greg Ravikovich and Eitan Har-Shoshanim examine how AI addresses the challenge of data overload in solar PV.

Systematic human inspection of the millions of source cutouts in the Hubble Legacy Archive is impossible – but artificial ...

Now, a research team led by Beihang University has unveiled the first high-throughput, non-destructive characterization of these precious materials, revealing that the "soil" on the lunar far side ...

You will be redirected to our submission process. In the era of big data, the growing diversity, dimensionality, and volume of data have accelerated the development of artificial intelligence (AI). In ...

To evaluate the diagnostic performance of semi-supervised learning models for aggressive prostate cancer detection on MRI compared to fully supervised models trained with additional expert annotations ...

Semi-supervised learning (SSL) aims to improve performance by exploiting unlabeled data when labels are scarce. Conventional SSL studies typically assume close environments where important factors ...

Recently, federated learning has been successfully applied in fields related to cyber-physical-social systems (CPSSs), owing to its ability to harness decentralized clients for training a global model ...

Abstract: Deep learning based methods have achieved extraordinary success in SAR automatic target recognition. However, deep learning conventionally necessitates a substantial number of labeled ...