Deep learning, which is a subfield of machine learning, has opened a new era for the
development of neural networks. The auto-encoder is a key component of deep structure …

Recently, deep learning has achieved great success in visual tracking. The goal of this
paper is to review the state-of-the-art tracking methods based on deep learning. First, we …

Anomaly detection in videos remains a challenging task due to the ambiguous definition of
anomaly and the complexity of visual scenes from real video data. Different from the …

Abstract Machine learning techniques are often used in computer vision due to their ability to
leverage large amounts of training data to improve performance. Unfortunately, most generic …

This paper presents a survey on the latest methods of moving object detection in video
sequences captured by a moving camera. Although many researches and excellent works …

Collaborative Robotics is one of the high-interest research topics in the area of academia
and industry. It has been progressively utilized in numerous applications, particularly in …

This article takes a problem-oriented perspective and presents a comprehensive review of
transfer-learning methods, both shallow and deep, for cross-dataset visual recognition …

Real-time video objects detection, tracking, and recognition are challenging issues due to
the real-time processing requirements of the machine learning algorithms. In recent years …

Existing deep trackers use deep convolutional neural networks to extract powerful features
or directly predict the position of the target. For most deep trackers, it is hard to improve their …

Most existing tracking methods are direct trackers, which directly exploit foreground or/and
background information for object appearance modeling and decide whether an image …