Recently, computer vision applications based on deep neural networks (DNN) have
developed rapidly. They are expected to be used in Internet-of-Things (IoT) systems such as …

Deep learning (DL) applications have attracted significant attention with the rapidly growing
demand for Internet of Things (IoT) systems. However, performing the inference tasks for DL …

Offloading the execution of complex Deep Neural Networks (DNNs) models to compute-
capable devices at the network edge, that is, edge servers, can significantly reduce capture …

With the rapid development of Internet of Things (IoTs), various sensors are deployed to
collect different physical information. Smart surveillance is one of applications by analyzing …

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

Deep learning-based visual analytic applications have drawn attention by suggesting fruitful
combinations with Deep Neural Network (DNN) models and visual data sensors. Because of …

Deep Neural Network (DNN) based video analytics empowers many computer vision-based
applications to achieve high recognition accuracy. To reduce inference delay and bandwidth …

Camera networks are essential to constructing fast and accurate mapping between virtual
and physical space for digital twin. In this paper, with the aim of developing energy-efficient …

Mobile video analytics applications, such as smart driving, VR/AR, and video surveillance,
have become increasingly popular due to the proliferation of mobile devices. These …

With the rise of artificial intelligence, various video analytics models have been applied in
many fields. Numerous studies are preoccupied with expanding the size of the model to …