Image Clustering
Image clustering is an unsupervised machine learning task aiming to group similar images together without pre-defined labels. Current research heavily emphasizes leveraging deep neural networks, often pre-trained on massive datasets, to extract robust image features, incorporating techniques like contrastive learning and incorporating external information such as text descriptions to improve semantic understanding and clustering accuracy. These advancements are improving the performance of image clustering across diverse applications, including art analysis, remote sensing, and even legal technology-assisted review, by enabling more efficient and accurate organization and analysis of large image datasets.
Papers
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