Deep learning has become a predominant method for solving data analysis problems in
virtually all fields of science and engineering. The increasing complexity and the large …

For robots to navigate and interact more richly with the world around them, they will likely
require a deeper understanding of the world in which they operate. In robotics and related …

Continuous learning has recently shown promising results for video analytics by adapting a
lightweight" expert" DNN model for each specific video scene to cope with the data drift in …

Edge-cloud collaborative video analytics is transforming the way data is being handled,
processed, and transmitted from the ever-growing number of surveillance cameras around …

Video analytics systems perform automatic events, movements, and actions recognition in a
video and make it possible to execute queries on the video. As a result of a large number of …

Abstract Machine Learning has played a major role in various applications including
Autonomous Vehicles and Intelligent Transportation Systems. Utilizing a deep convolutional …

Visual surveillance systems have recently captured the attention of the research community.
Most of the proposed surveillance systems deal with stationary cameras. Nevertheless …

The proliferation of multimedia devices over the Internet of Things (IoT) generates an
unprecedented amount of data. Consequently, the world has stepped into the era of big …

While large deep neural networks excel at general video analytics tasks, the significant
demand on computing capacity makes them infeasible for real-time inference on resource …

Computer Vision has played a major role in Intelligent Transportation Systems (ITS) and
traffic surveillance. Along with the rapidly growing automated vehicles and crowded cities …