This work addresses the problem of domain adaptation and generalization in a unified
fashion. The main idea is to exploit the siamese architecture with the Contrastive Loss to …

The goal of person reidentification (Re-ID) is to identify a given pedestrian from a network of
nonoverlapping surveillance cameras. Most existing works follow the supervised learning …

Traditionally, abnormal heart sound classification is framed as a three-stage process. The
first stage involves segmenting the phonocardiogram to detect fundamental heart sounds; …

The rapid proliferation of user generated content has given rise to large volumes of text
corpora. Increasingly, scholars, researchers, and organizations employ text classification to …

This article provides a novel framework for single-domain generalized object detection (ie,
Single-DGOD), where we are interested in learning and maintaining the semantic structures …

Recently, many real-world applications exploit multi-view data, which is collected from
diverse domains or obtained from various feature extractors and reflect different properties …

In this paper, we propose a new Dividing and Aggregating Network (DA-Net) for multi-view
action recognition. In our DA-Net, we learn view-independent representations shared by all …

Fine-grained image classification, which targets at distinguishing subtle distinctions among
various subordinate categories, remains a very difficult task due to the high annotation cost …

Domain adaption (DA) and domain generalization (DG) are two closely related methods
which are both concerned with the task of assigning labels to an unlabeled data set. The …

The meaningful patterns embedded in high-dimensional multi-view data sets typically tend
to have a much more compact representation that often lies close to a low-dimensional …