… Aiming at the problems of tedious feature extraction with low accuracy and traditional
deep learning network could not extract the hidden information of data comprehensively, an …

… ‘The integration of AI, machine learning, and big data analytics can significantly improve
the ability of nuclear warfare systems to locate, track, target, and destroy an enemy’s nuclear …

… in wireless sensor networks, underwater sensor networks have become a new hot research
area. Underwater sensor networks … tasks such as oceanographic data collection, pollution …

… business risk factors in a range of industrial sectors [1]. This study uses both federated learning
and machine learning … an ad hoc wireless sensor network in which multiple sensor nodes …

… for sensor network applications. According to the scheme, important studies can generally
be categorized into classes: observable model-based … detection in wireless sensor networks. …

… that performs instance decision making and reduces unnecessary data transfer to the cloud,
… Jain, Machine learning based network vulnerability analysis of industrial internet of things, …

… Things (IoT), predictive analytics, and machine learning has ushered in a … data from IoT
sensors and satellites, applies predictive analytics, and harnesses the power of machine learning …

… propose the security architecture of sensor networks in this paper, … intrusion-tolerant routing
in wireless sensor networks In: Proc. of … areas are computer networks and machine learning. …

… years and a spike in data availability [6]. Therefore, the DL-based methods, eventually,
outperformed … Thus, in this work, we focus on applying deep learning methods to medical image …

… Therefore, this study aims to develop a deep learning-based identification and prediction
method for machining inspection. This method is implemented in two tasks that are typical in …