Deep clustering: A comprehensive survey
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 …
a good data representation is crucial for clustering algorithms. Recently, deep clustering …
Artificial intelligence (AI) in augmented reality (AR)-assisted manufacturing applications: a review
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 …
cognitive load by bridging the gap between the task-at-hand and relevant information by …
Deep clustering for unsupervised learning of visual features
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 …
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
The usage of convolutional neural networks (CNNs) for unsupervised image segmentation
was investigated in this study. Similar to supervised image segmentation, the proposed CNN …
was investigated in this study. Similar to supervised image segmentation, the proposed CNN …
Deep clustering via joint convolutional autoencoder embedding and relative entropy minimization
In this paper, we propose a new clustering model, called DEeP Embedded RegularIzed
ClusTering (DEPICT), which efficiently maps data into a discriminative embedding subspace …
ClusTering (DEPICT), which efficiently maps data into a discriminative embedding subspace …
Multi-view clustering: A survey
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 …
views. These data are referred to as multi-view data. Unleashing the power of knowledge in …
A comprehensive survey of clustering algorithms
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 …
communication science, computer science and biology science. Clustering, as the basic …
Learning discrete representations via information maximizing self-augmented training
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 …
compactness of the representations and ease of interpretation. The task includes clustering …
Unsupervised and semi-supervised learning with categorical generative adversarial networks
JT Springenberg - ar**, deep clustering has shown
impressive ability to deal with unsupervised learning for structure analysis of high …
impressive ability to deal with unsupervised learning for structure analysis of high …