Video, as a key driver in the global explosion of digital information, can create tremendous
benefits for human society. Governments and enterprises are deploying innumerable …

Edge computing has been getting a momentum with ever-increasing data at the edge of the
network. In particular, huge amounts of video data and their real-time processing …

The falling cost of IoT cameras, the advancement of AI-based computer vision algorithms,
and powerful hardware accelerators for deep learning have enabled the widespread …

Video analytics with deep learning techniques has generated immense interest in academia
and industry, captivating minds with its transformative potential. Deep learning techniques …

With the installation of enormous public safety and transportation infrastructure cameras,
video analytics has come to play an essential part in public safety. Typically, video analytics …

Edge video analytics is becoming the solution to many safety and management tasks. Its
wide deployment, however, must first address the tension between inference accuracy and …

Deep learning with Deep Neural Networks (DNNs) can achieve much higher accuracy on
many computer vision tasks than classic machine learning algorithms. Because of the high …

Cloud computing and edge computing models are popularly applied in emerging
applications, such as smart homes, smart parks, and connected autonomous vehicles for …

Recent advances in machine learning and deep learning have enabled many existing
applications in smart cities, autonomous systems, and wearable devices. These applications …

Deep neural network (DNN)-based video processing methods are applied in mobile video
analytics because of high accuracy. Edge computing is an efficient paradigm that improves …