Artificial intelligence models play a crucial role in monitoring and maintaining railroad
infrastructure by analyzing image data of foreign objects on power transmission lines …

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 …

Accurate and rapid weed detection is important step for crop precision management.
Existing deep learning based weed detection algorithms often have huge number of …

With the rapid growth of aerial image quantity and quality, the performance of aerial scene
classifiers based on deep learning models has also achieved tremendous success …

To address the low-light image (LLI) problem in train driving scenarios, this paper proposes
a progressive and lightweight network called BrightsightNet for LLI enhancement. First, to …

In classical machine learning algorithms, used in many analysis tasks, the data are
centralized for training. That is, both the model and the data are housed within one device …

To address the challenge of precise foreign object detection on railway tracks, this study
proposes RailSegVITNet, an efficient deep learning-based model that aims to accurately …

Object detection in remote sensing imagery exhibits difficulties due to complex backgrounds,
diverse object scales, and intricate spatial context relationships. Motivated by the problems …

We aimed to research the design and path-planning methods of an intelligent disinfection-
vehicle system. A ROS (robot operating system) system was utilized as the control platform …

Almost all existing distribution network grounding tests are online. The existing offline
distribution network grounding detection methods are all manual handling methods, which …