Representing hyperspectral images (HSIs) is a complex and challenging task, primarily due to spectral uncertainty. The learnable prototypical contrastive learning is specialized in discriminative ...

Recently, contrastive learning (CL) has shown excellent performance in the hyperspectral image (HSI) classification. However, existing CL-based methods face two specific challenges: 1) multiview ...

Considering that the chemical reaction space can be hierarchically organized and the classification labels are freely accessible, we propose a framework called knowledge-induced hierarchical ...

Contrastive Learning With Dynamic Instances and Contour Consistency for SAR Land-Cover Classification Foundation Model - SARpre-train/DIC3L ...

Hongwei Li’s team from China University of Geosciences published a research article titled “scSCC: A swapped contrastive ...

CONTAIN™ represents the next breakthrough in AI-powered ore sorting from TOMRA Mining – a deep learning solution purpose-built to classify complex inclusion-type ores with unprecedented accuracy. By ...

Machine learning methods enable computers to learn without being explicitly programmed and have multiple applications, for example, in the improvement of data mining algorithms.

The substantial increase in mental health disorders globally necessitates scalable, accurate tools for detecting and classifying these conditions in digital environments. This study addresses the ...

Uncover the best learning management systems of 2025. Compare leading platforms to enhance your online education experience and boost learner engagement.

Business schools are redesigning their curricula to produce graduates who interpret machine learning models, and make critical decisions in data-rich environments ...

Phil Hello. This is 6 Minute English from BBC Learning English. I’m Phil. Georgie And I’m Georgie. For me, there’s nothing like reading a book – I love turning the pages and the smell of ...