A comprehensive survey of image clustering based on deep learning

Abstract

Deep clustering refers to the integration of deep learning techniques with clustering. With the popularity of social media, deep clustering for image data has attracted widespread attention from researchers. This paper provides a comprehensive review of the latest research image clustering based on deep learning. First, image clustering is categorized into two main types: self-supervised learning-based and semi-supervised learning-based methods. The paper analyzes and summarizes the methods in each category, highlighting their advantages and disadvantages. Next, the paper compares and analyzes representative methods through experimental results, providing insights for future research and practical applications. Finally, the paper discusses existing challenges and presents potential directions for future research.