ArticleHeliyon2024
Foreign object detection in urban rail transit based on deep differentiation segmentation neural network.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- Wavelet-Based Health Monitoring Approach for Train Door Actuation Using Motor Current Analysis.Sensors (Basel, Switzerland) · 2026Article
- Real-Time Low-Cost Traffic Monitoring Based on Quantized Convolutional Neural Networks for the CNOSSOS-EU Noise Model.Sensors (Basel, Switzerland) · 2026Article
- Graph-Based and Multi-Stage Constraints for Hand-Object Reconstruction.Sensors (Basel, Switzerland) · 2026Article
- A Fusion Algorithm for Pedestrian Anomaly Detection and Tracking on Urban Roads Based on Multi-Module Collaboration and Cross-Frame Matching Optimization.Sensors (Basel, Switzerland) · 2026Article
- Enhancing Point Cloud Registration for Pipe Fittings: A Coarse-to-Fine Approach with DANIP Keypoint Detection and ICP Optimization.Sensors (Basel, Switzerland) · 2025Article
- Design and Implementation of a YOLOv2 Accelerator on a Zynq-7000 FPGA.Sensors (Basel, Switzerland) · 2025Article
- Radar-Camera Fusion in Perspective View and Bird's Eye View for 3D Object Detection.Sensors (Basel, Switzerland) · 2025Article
- Railway Intrusion Risk Quantification with Track Semantic Segmentation and Spatiotemporal Features.Sensors (Basel, Switzerland) · 2025Article
- COSMICA: A Novel Dataset for Astronomical Object Detection with Evaluation Across Diverse Detection Architectures.Journal of imaging · 2025Article
- YOLO-BCD: A Lightweight Multi-Module Fusion Network for Real-Time Sheep Pose Estimation.Sensors (Basel, Switzerland) · 2025Article
- The reconstruction method for static exterior model of digital twin railway station based on mobile vehicle.Scientific reports · 2025Article
- DP-YOLO: A Lightweight Real-Time Detection Algorithm for Rail Fastener Defects.Sensors (Basel, Switzerland) · 2025Article
- Automatic detection of foreign object intrusion along railway tracks based on MACENet.PloS one · 2025Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
With the increasing scale of urban rail transit, foreign object intrusion has become a significant operational safety hazard in urban rail transit. Although the laser-based automatic foreign object detection system has advantages such as long-distance detection and insensitivity to light changes, it has drawbacks such as large blind spots and low visualization. In response to the problems existing in laser detection systems, we proposed a novel video-based deep differentiation segmentation neural network for foreign object detection. Firstly, the foreign object detection is transformed into a binary classification problem, and the foreign object is determined as the image's foreground using image segmentation principles. Secondly, build a deep segmentation network based on deep convolution. Finally, perform morphological operations and threshold judgment on the foreground segmentation image to filter out the final detection results. To improve the detection effect, we reduced the impact of airflow disturbance by sampling and calculating the average background image. At the same time, the channel attention model and spatial attention model are added to the deep differentiation neural network. Collecting real data on subway platforms for experiments shows that the proposed method has a detection accuracy of 95.8 %, which is superior to traditional detection methods and recent image segmentation neural networks.
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