… In this research work, a deep learning-based intrusion detection system for an IoT- multi-cloud
environment is presented that integrates the end-user applications and identifies the …

… For example, IoT devices such as cameras are generating a huge amount of images when …
based deep model for automatic face recognition in a cloud environment. The proposed deep …

… merging cloud and edge computing for IoT data analytics and presents a deep learning-based
approach for data reduction on the edge with the machine learning on the cloud. The …

… In the future, we will further study more deep learning schemes to enhance the detection
accuracy and efficiency in the edge computing environment. More evaluations in different …

… of the most recent works involving the convergence of deep learning with various computing
paradigms, including cloud, fog, edge, and IoT, in this contribution. We also draw attention …

… /cloud nodes, and optimize traffic rates of these services going through physical nodes. Our
model aims to state that placing IoT … We argue that a deep learning method can be a novel …

… An IoT application as smart traffic model reported in [11] accurately predicts the traffic using
… in the context of IoT cloud environment. Similarly, the application of IoT cloud integration in …

… cloud computing with IoT data analytics. The main contributions are the reduction of network
traffic and latencies for machine learning (… between IoT devices and the cloud reducing the …

… city IoT applications. However, how to customize deep learning techniques for task offloading
in IoT is … In this article, the motivation of designing a distributed deep learning-driven task …

… Internet of Things confers seamless connectivity between people and objects, and its confluence
with the Cloud … artificial intelligence and machine learning approaches permeating the …