Although current deep learning models for bearing fault diagnosis have achieved excellent
accuracy, the lack of constraint-guided learning of the physical mechanisms of real bearing …

Multi-Objective Multi-Camera Tracking (MOMCT) is aimed at locating and identifying
multiple objects from video captured by multiple cameras. With the advancement of …

Autonomous driving is an important branch of artificial intelligence, and real-time and
accurate object detection is key to ensuring the safe and stable operation of autonomous …

To segment railway track regions in real-time for intrusion detection and improving security,
this paper proposes an efficient railway track region segmentation network (ERTNet) based …

Vehicle detection is an important component of intelligent transportation systems and
autonomous driving. However, in real-world vehicle detection scenarios, the presence of …

In urban smart city environments, traffic hazards can lead to catastrophic outcomes,
including significant property losses and severe threats to public safety. Conventional traffic …

This study proposed a performance-interpretable deep learning model for rolling bearing
fault diagnosis that integrates an intelligent fusion of sound and vibration signals and self …

This study proposes an efficient rolling bearing fault diagnosis model of a hybrid neural
network with a lightweight attention mechanism. Firstly, to achieve the low complexity of …

The major problem in Thailand related to parking is time violation. Vehicles are not allowed
to park for more than a specified amount of time. Implementation of closed-circuit television …

Object detection and image recognition are some of the most significant and challenging
branches in the field of computer vision. The prosperous development of unmanned driving …