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 …

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

In actual processing plants, the quality and efficiency of the traditional spiral slope flow
concentrator still rely on workers to observe the changes in the mineral belt. However, in …

Background Agar plate analysis is vital for microbiological testing in industries like food,
pharmaceuticals, and biotechnology. Manual inspection is slow, laborious, and error-prone …

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 …

Abstract Accurate delineation of Gross Tumor Volume (GTV) is crucial for radiotherapy.
Deep learning-driven GTV segmentation technologies excel in rapidly and accurately …

This paper introduces a solution to address the intricacy of the model employed in the deep
learning-based diagnosis of musculoskeletal abnormalities and the limitations observed in …

The existing foreign object recognition methods have some limitations, such as imprecise
extraction of railway regions and limited real-time performance. This study proposes a …

This paper describes the development and evaluation of a surveillance system for the
detection of people and objects on railroad tracks in real time. Firstly, the paper evaluates …