Deep Clustering

Deep Clustering is a clustering method based on deep learning, designed to automatically learn high-dimensional representations of data through neural networks to achieve more effective unsupervised clustering. This method optimizes the network to minimize the similarity between different clusters and maximize the similarity within the same cluster, thereby improving the accuracy and robustness of clustering. Deep Clustering has significant application value in processing multimodal data such as images, text, and audio, effectively uncovering the intrinsic structure and patterns of data, and supporting efficient analysis and understanding of complex datasets.