Support Vector Machines (SVMs) have become a cornerstone of machine learning, widely adopted for their robustness in classification and regression tasks across diverse fields ranging from remote ...
Örebro researchers Rajesh Patil and Professor Magnus Löfstrand have developed an AI system that detects welding defects, ...
The core idea of LCQHNN is to center on quantum feature amplification (Quantum Feature Amplification) while combining a classical stability optimization strategy, establishing an efficient information ...
A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...
This is the Best of the Week. Voices from the Analytical Front Line: Bingchuan Wei on Chromatography in 2026 In the year 2026, chromatography is undergoing a series of advancements and challenges.
A recent analysis of a major developmental dataset reveals that children who play musical instruments over several years ...
Wearable technology could transform injury detection in workplaces, but researchers highlight the current limits of automation in ergonomic risk assessment.
Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...
ScyllaDB today announced the general availability of its new Vector Search capability, which is integrated into ScyllaDB X Cloud. This high-performance vector search supports the industry’s largest ...