Human activity recognition (HAR) systems attempt to automatically identify and analyze
human activities using acquired information from various types of sensors. Although several …

In practical applications, multi-view data depicting objects from assorted perspectives can
facilitate the accuracy increase of learning algorithms. However, given multi-view data, there …

An important underlying assumption that guides the success of the existing multiview
learning algorithms is the full observation of the multiview data. However, such rigorous …

In real-world applications, it is often that the collected multi-view data are incomplete, ie,
some views of samples are absent. Existing clustering methods for incomplete multi-view …

In this paper, we propose a general framework for incomplete multiview clustering. The
proposed method is the first work that exploits the graph learning and spectral clustering …

The counting and identification of white blood cells (WBCs, ie, leukocytes) in blood smear
images play a crucial role in the diagnosis of certain diseases, including leukemia …

Occluded person re-identification (re-ID) presents a challenging task due to occlusion
perturbations. Although great efforts have been made to prevent the model from being …

Palmprint recognition has been widely applied to security authentication due to its rich
characteristics, ie, local direction, wrinkle, and texture. However, different types of palmprint …

Multi-view semi-supervised classification is inherently a challenging task in multi-view
learning due to the lack of label information. Existing methods generally suffer from …

Recently, finger-based multimodal biometrics, due to its high security and stability, has
received considerable attention compared with unimodal biometrics. However, existing …