Nature

Self-supervised learning for remote sensing scene classification under the few shot scenario

Scene classification is a crucial research problem in remote sensing (RS) that has attracted many researchers recently. It has many challenges due to multiple issues, such as: the complexity of remote ...
Nature

A Cluster-then-label Semi-supervised Learning Approach for Pathology Image Classification

Completely labeled pathology datasets are often challenging and time-consuming to obtain. Semi-supervised learning (SSL) methods are able to learn from fewer labeled data points with the help of a ...
Frontiers

Dual contextual learning for semi-supervised medical image classification

Semi-supervised learning (SSL) has emerged as a promising paradigm for medical image classification, addressing the critical challenge of limited labeled data in healthcare where expert annotation is ...
IEEE

Exploring Beyond Logits: Hierarchical Dynamic Labeling Based on Embeddings for Semi ...

Abstract: In semi-supervised learning, methods that rely on confidence learning to generate pseudo-labels have been widely proposed. However, increasing research finds that when faced with noisy and ...