Abstract The problem of Multiple Object Tracking (MOT) consists in following the trajectory of
different objects in a sequence, usually a video. In recent years, with the rise of Deep …

There have been tremendous improvements in deep learning and reinforcement learning
techniques. Automating learning and intelligence to the full extent remains a challenge. The …

Reinforcement learning (RL) is gaining a foothold in artificial intelligence-based research
academia. More and more applications are coming to fore where RL is being applied in a …

Traffic analysis using computer vision techniques is attracting more attention for the
development of intelligent transportation systems. Consequently, counting traffic volume …

The significant growth of surveillance camera networks necessitates scalable AI solutions to
efficiently analyze the large amount of video data produced by these networks. As a typical …

There is an increasing demand on utilizing camera equipped drones and their applications
in many domains varying from agriculture to entertainment and from sports events to …

Object tracking is a computer vision task that aims to locate and continuously follow the
movement of an object in video frames, given an initial annotation. Despite its importance …

CNN (convolutional neural network) based real time trackers usually do not carry out online
network update in order to maintain rapid tracking speed. This inevitably influences the …

This paper aims at highlighting cutting-edge research results in the field of visual tracking by
deep reinforcement learning. Deep reinforcement learning (DRL) is an emerging area …

Traffic flow analysis in complex areas (eg, intersections and roundabouts) plays an
important part in the development of intelligent transportation systems. Among several …