Multiple imaging modalities can be combined to provide more information about the real
world than a single modality alone. Infrared images discriminate targets with respect to their …

Considering the labeled samples may be difficult to obtain because they require human
annotators, special devices, or expensive and slow experiments. Semi-supervised learning …

In this paper, we propose a new infrared and visible image fusion method based on multi-
scale transformation and norm optimization. In this method, a new loss function is designed …

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 …

Image decomposition is crucial for many image processing tasks, as it allows to extract
salient features from source images. A good image decomposition method could lead to a …

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 …

Abstract The Artificial Intelligence Internet of Things (AIoT) is an emerging concept aiming to
perceive, understand and connect the 'intelligent things' to make the intercommunication of …

Multi-view clustering has attracted intensive attention due to the effectiveness of exploiting
multiple views of data. However, most existing multi-view clustering methods only aim to …

This paper studies the subspace clustering problem. Given some data points approximately
drawn from a union of subspaces, the goal is to group these data points into their underlying …

Multiview data clustering attracts more attention than their single-view counterparts due to
the fact that leveraging multiple independent and complementary information from multiview …