Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …

In recent years, the popularity of depth sensors and 3D scanners has led to a rapid
development of 3D point clouds. Semantic segmentation of point cloud, as a key step in …

Landslides pose a constant threat to the lives and property of mountain people and may also
cause geomorphological destruction such as soil and water loss, vegetation destruction, and …

It is difficult to identify similar apples diseases due to the complicated changes in color and
texture of diseased parts. In order to solve this problem, an Internet of Things (IoT) system for …

In this study, a hybrid deep belief network (DBN) cyber intrusion detection system was
proposed to provide a secure network by controlling network traffic in Industrial control …

In this paper, we propose a Deep Belief Network (DBN) based approach for the
classification of audio signals to improve work activity identification and remote surveillance …

Urban scene-level 3D point cloud labeling is a very laborious and expensive task compared
to images. Conversely however, image processing techniques, deep learning or otherwise …

Abstract Autonomous Driving Vehicle (ADV) services have become a prominent motif in
intelligent vehicle technology by adapting deep learning features. Automated driverless …

An improved unsupervised deep belief network (DBN), namely median filtering deep belief
network (MFDBN) model is proposed in this paper through median filtering (MF) for bearing …

Research on data-driven fault diagnosis methods has received much attention in recent
years. The deep belief network (DBN) is a commonly used deep learning method for fault …