Deep Neural Networks (DNN) has been widely applied in big data-driven Internet of Things
(IoT) for excellent learning ability, while the black-box nature of DNN leads to uncertainty of …

Convolutional neural networks (CNNS) enable machines to view the world as humans and
become increasing prevalent for Internet of Things (IoT) applications. Instead of streaming …

Collaborative inference is a promising method for balancing the limited computational power
of Internet of Things (IoT) devices with the huge computational demands of convolutional …

With the vigorous development of artificial intelligence (AI), intelligence applications based
on deep neural networks (DNNs) have changed people's lifestyles and production …

Deep Neural Networks (DNNs) have been widely applied in Internet of Things (IoT) systems
for various tasks such as image classification and object detection. However, heavyweight …

With the revolution of smart industry, more and more Industrial Internet of Things (IIoT)
devices as well as AI algorithms are deployed to achieve industrial intelligence. While …

Deep learning technologies are empowering IoT devices with an increasing number of
intelligent services. However, the contradiction between resource-constrained IoT devices …

With the widespread application of artificial intelligence and the Internet of Things, the
intellectualization of the industrial Internet of Things (IIoT) has received more and more …

Deep Neural Networks (DNNs) are widely used to analyze the abundance of data collected
by massive Internet-of-Thing (IoT) devices. The traditional approaches usually send the data …

For fast and accurate Convolutional Neural Network (CNN) inference of massive Internet of
Things (IoT) data, Collaborative Inference (CI) based on partition and compression …