Zero-shot remote sensing scene classification aims to solve the scene classification problem
on unseen categories and has attracted numerous research attention in the remote sensing …

The recently proposed FixMatch achieved state-of-the-art results on most semi-supervised
learning (SSL) benchmarks. However, like other modern SSL algorithms, FixMatch uses a …

Pseudo labeling and consistency regularization approaches with confidence-based
thresholding have made great progress in semi-supervised learning (SSL). In this paper, we …

Recent self-supervised methods for image representation learning are based on maximizing
the agreement between embedding vectors from different views of the same image. A trivial …

Semi-supervised learning (SSL) improves model generalization by leveraging massive
unlabeled data to augment limited labeled samples. However, currently, popular SSL …

Detecting out-of-distribution (OOD) samples is crucial for ensuring the safety of machine
learning systems and has shaped the field of OOD detection. Meanwhile, several other …

Training machine learning models in a meaningful order, from the easy samples to the hard
ones, using curriculum learning can provide performance improvements over the standard …

State-of-the-art deep learning models are often trained with a large amount of costly labeled
training data. However, requiring exhaustive manual annotations may degrade the model's …

In this paper, we address the problem of generalized category discovery (GCD), ie, given a
set of images where part of them are labelled and the rest are not, the task is to automatically …

Abstract Generalized Category Discovery (GCD) aims to discover novel categories in
unlabelled datasets using knowledge learned from labelled samples. Previous studies …