microCLIP is a lightweight self-training framework that adapts CLIP for fine-grained image classification without requiring labeled data. While CLIP is strong in zero-shot transfer, it primarily ...

Abstract: Unsupervised classification plays an important role in understanding polarimetric synthetic aperture radar (PolSAR) images. One of the typical representations of PolSAR data is in the form ...

Deep learning techniques have been successfully applied to object classification in Synthetic Aperture Radar (SAR) images, achieving remarkable performance. However, the current Transformer ...

Abstract: This paper presents a novel unsupervised image classification method for polarimetric synthetic aperture radar (PolSAR) data. The proposed method is based on a discriminative clustering ...

For many computer vision tasks (e.g., image classification, object detection), existing deep learning-based models usually suffer from significant performance degradation when directly applying them ...

Faculty of Advanced Engineering, Tokyo University of Science, Tokyo 125-8585, Japan ...

In response to the problem of inadequate utilization of local information in PolSAR image classification using Vision Transformer in existing studies, this paper proposes a Vision Transformer method ...

Ilya Sutskever, co-founder of OpenAI, explains why unsupervised learning works and how it relates to supervised learning. The core concept is compression - good compressors can become good predictors.

The wet-dog shake behavior (WDS) is a short-duration behavior relevant to the study of various animal disease models, including acute seizures, morphine abstinence, and nicotine withdrawal. However, ...