We consider the problem of detecting objects, as they come into view, from videos in an
online fashion. We provide the first real-time solution that is guaranteed to minimize the …

Emerging Internet of Things (IoT) and mobile computing applications are expected to
support latency-sensitive deep neural network (DNN) workloads. To realize this vision, the …

The concept of the Internet of Things (IoT) is a reality now. This paradigm shift has caught
everyones attention in a large class of applications, including IoT-based video analytics …

Visual perception is critical and essential to understand phenomenon and environments of
the world. Pervasively configured devices like cameras are key in dynamic status …

In this paper, a real-time deep learning-based framework for detecting and tracking
Unmanned Aerial Vehicles (UAVs) in video streams captured by a fixed-wing UAV is …

The Internet of Things (IoT) devices such as sensors and video cameras have small
memories and less computational power. The video analytics of traditional approaches for …

With the growing use of wireless surveillance cameras in (Internet of things) IoT applications
the need to address storage capacity and transmission bandwidth challenges becomes …

Adaptive and efficient computer vision systems have been proposed to make computer
vision tasks, eg, object classification and object detection, optimized for embedded boards …

Transferring image-based object detectors to the domain of video remains challenging
under resource constraints. Previous efforts utilised optical flow to allow unchanged features …

Recent advances in computer vision and neural networks have made it possible for more
surveillance videos to be automatically searched and analyzed by algorithms rather than …