In recent years, unsupervised feature selection methods have raised considerable interest in
many research areas; this is mainly due to their ability to identify and select relevant features …

Automatic target recognition (ATR) for military applications is one of the core processes
toward enhancing intelligence and autonomously operating military platforms. Spurred by …

Subspace clustering is an effective method that has been successfully applied to many
applications. Here, we propose a novel subspace clustering model for multi-view data using …

In this paper, we propose a novel Latent Multi-view Subspace Clustering (LMSC) method,
which clusters data points with latent representation and simultaneously explores underlying …

Previous multi-view clustering algorithms mostly partition the multi-view data in their original
feature space, the efficacy of which heavily and implicitly relies on the quality of the original …

Multi-view clustering is a long-standing important task, however, it remains challenging to
exploit valuable information from the complex multi-view data located in diverse high …

Epilepsy recognition based on electroencephalogram (EEG) and artificial intelligence
technology is the main tool of health analysis and diagnosis in Internet of medical things …

Person re-identification has been widely studied due to its importance in surveillance and
forensics applications. In practice, gallery images are high-resolution (HR) while probe …

In this paper, we design a Deep Dual-Domain (D3) based fast restoration model to remove
artifacts of JPEG compressed images. It leverages the large learning capacity of deep …

Multi-view subspace clustering, which aims to partition a set of multi-source data into their
underlying groups, has recently attracted intensive attention from the communities of pattern …