Metric learning aims to measure the similarity among samples while using an optimal
distance metric for learning tasks. Metric learning methods, which generally use a linear …

The science of solving clinical problems by analyzing images generated in clinical practice
is known as medical image analysis. The aim is to extract information in an affective and …

Surveillance videos are able to capture a variety of realistic anomalies. In this paper, we
propose to learn anomalies by exploiting both normal and anomalous videos. To avoid …

Person re-identification is a challenging task mainly due to factors such as background
clutter, pose, illumination and camera point of view variations. These elements hinder the …

In the past few years, the field of computer vision has gone through a revolution fueled
mainly by the advent of large datasets and the adoption of deep convolutional neural …

Feature extraction and matching are two crucial components in person Re-Identification
(ReID). The large pose deformations and the complex view variations exhibited by the …

Automated Facial Expression Recognition (FER) in the wild using deep neural networks is
still challenging due to intra-class variations and inter-class similarities in facial images …

Person re-identification (ReID) is an important task in wide area video surveillance which
focuses on identifying people across different cameras. Recently, deep learning networks …

In this paper, we address the problem of person re-identification, which refers to associating
the persons captured from different cameras. We propose a simple yet effective human part …

Person re-identification (ReID) is to identify pedestrians observed from different camera
views based on visual appearance. It is a challenging task due to large pose variations …