In the era of big data, the growing diversity, dimensionality, and volume of data have accelerated the development of artificial intelligence (AI). In turn, ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Enterprise adoption of cognitive intelligence platforms has accelerated, yet executive confidence has not kept pace. Many deployments promise ...

Proposed as an alternative to chemical mechanical polishing (CMP), in which abrasive particles are dispersed in liquid, the method uses vertically aligned carbon nanotubes fixed in polyurethane and ...

University of Surrey as a Lecturer in Robotics and is a Royal Society Short Industry Fellow. His research focuses on robotic perception, learning, and collaboration, approaching these challenges ...

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 ...

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

BEIJING, Oct. 15, 2025 /PRNewswire/ -- WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, they announced the ...

Abstract: Existing magnetic anomaly detection (MAD) methods are widely categorized into target-, noise-, and machine learning-based methods. This article first analyzes the commonalities and ...

A research team led by Prof. WANG Huanqin at the Institute of Intelligent Machines, the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, recently proposed a semi-supervised ...