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

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 …

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

The automation strategy of today's smart cities relies on large IoT (internet of Things)
systems that collect big data analytics to gain insights. Although there have been recent …

The advancements and progress in artificial intelligence (AI) and machine learning, and the
numerous availabilities of mobile devices and Internet technologies together with the …

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

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 …

The multifarious video contents generated through various applications is growing
exponentially resulting in huge volumes. Analyzing these contents manually is a …

In smart city scenarios, the huge proliferation of monitoring cameras scattered in public
spaces has posed many challenges to network and processing infrastructure. A few dozen …

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 …