The key to address clothes-changing person re-identification (re-id) is to extract clothes-
irrelevant features, eg, face, hairstyle, body shape, and gait. Most current works mainly focus …

Advances in multisource remote sensing have allowed for the development of more
comprehensive observation. The adoption of deep convolutional neural networks (CNN) …

In this paper, we present an efficient spatial-temporal representation for video person re-
identification (reID). Firstly, we propose a Bilateral Complementary Network (BiCnet) for …

Person re-identification is a challenging research issue in computer vision and has a broad
application prospect in intelligent security. In recent years, with the emergence of large-scale …

Breast histology image classification is a crucial step in the early diagnosis of breast cancer.
In breast pathological diagnosis, Convolutional Neural Networks (CNNs) have …

Person re-identification (ReID) aims to find the person of interest across multiple non-
overlap** cameras. It is considered an essential step for person tracking applications …

We present a novel model for left ventricle endocardium segmentation from
echocardiography video, which is of great significance in clinical practice and yet a …

Video person re-identification (V-ReID) can leverage rich spatial-temporal information
embedded in sequence data to achieve better accuracy. However, it is vulnerable to the …

People live in a 3D world. However, existing works on person re-identification (re-id) mostly
consider the semantic representation learning in a 2D space, intrinsically limiting the …

Fatigue driving is a significant cause of road traffic accidents and associated casualties.
Automatic assessment of driver drowsiness by monitoring electroencephalography (EEG) …