Model evaluation measures how well a trained machine learning model performs on unseen data, while validation guides tuning during development. Best practice involves splitting data into training, ...

Tensor representation (TR) can sensitively perceive the inherent prior structure of hyperspectral images, showing broad prospects in hyperspectral anomaly detection (HAD). However, current models are ...

There is a persistent belief in the ‘AI’ community that large language models (LLMs) have the ability to learn and self-improve by tweaking the weights in their vector space. Although ...

The rapid advances in machine learning (ML) and artificial intelligence (AI) are transforming biology and opening new directions for scientific inquiry.