Deep clustering: A comprehensive survey

Y Ren, J Pu, Z Yang, J Xu, G Li, X Pu… - IEEE transactions on …, 2024‏ - ieeexplore.ieee.org
Cluster analysis plays an indispensable role in machine learning and data mining. Learning
a good data representation is crucial for clustering algorithms. Recently, deep clustering …

Artificial intelligence (AI) in augmented reality (AR)-assisted manufacturing applications: a review

CK Sahu, C Young, R Rai - International Journal of Production …, 2021‏ - Taylor & Francis
Augmented reality (AR) has proven to be an invaluable interactive medium to reduce
cognitive load by bridging the gap between the task-at-hand and relevant information by …

Deep clustering for unsupervised learning of visual features

M Caron, P Bojanowski, A Joulin… - Proceedings of the …, 2018‏ - openaccess.thecvf.com
Clustering is a class of unsupervised learning methods that has been extensively applied
and studied in computer vision. Little work has been done to adapt it to the end-to-end …

Unsupervised learning of image segmentation based on differentiable feature clustering

W Kim, A Kanezaki, M Tanaka - IEEE Transactions on Image …, 2020‏ - ieeexplore.ieee.org
The usage of convolutional neural networks (CNNs) for unsupervised image segmentation
was investigated in this study. Similar to supervised image segmentation, the proposed CNN …

Deep clustering via joint convolutional autoencoder embedding and relative entropy minimization

K Ghasedi Dizaji, A Herandi, C Deng… - Proceedings of the …, 2017‏ - openaccess.thecvf.com
In this paper, we propose a new clustering model, called DEeP Embedded RegularIzed
ClusTering (DEPICT), which efficiently maps data into a discriminative embedding subspace …

Multi-view clustering: A survey

Y Yang, H Wang - Big data mining and analytics, 2018‏ - ieeexplore.ieee.org
In the big data era, the data are generated from different sources or observed from different
views. These data are referred to as multi-view data. Unleashing the power of knowledge in …

A comprehensive survey of clustering algorithms

D Xu, Y Tian - Annals of data science, 2015‏ - Springer
Data analysis is used as a common method in modern science research, which is across
communication science, computer science and biology science. Clustering, as the basic …

Learning discrete representations via information maximizing self-augmented training

W Hu, T Miyato, S Tokui, E Matsumoto… - … on machine learning, 2017‏ - proceedings.mlr.press
Learning discrete representations of data is a central machine learning task because of the
compactness of the representations and ease of interpretation. The task includes clustering …