Research on Two-Stage Railway Intrusion Detection Using Enhanced U-Net and YOLOv11
- 2 August 2026
- book chapter
- Published by Springer Nature
- p. 532-539
Abstract
No abstract availableKeywords
This publication has 11 references indexed in Scilit:
- SCSegamba: Lightweight Structure-Aware Vision Mamba for Crack Segmentation in Structures2025
- RailGoerl24: Görlitz Rail Test Center CV Dataset 20242025
- LEFuse: Joint low-light enhancement and image fusion for nighttime infrared and visible imagesNeurocomputing, 2025
- A real-time foreign object detection method based on deep learning in complex open railway environmentsJournal of Real-Time Image Processing, 2024
- A Dense Attention Railway Foreign Object Detection Algorithm Based on Mask R-CNNIEEE Access, 2024
- Efficient railway track region segmentation algorithm based on lightweight neural network and cross-fusion decoderAutomation in Construction, 2023
- Rail Surface Defect Detection Based on Improved UPerNet and Connected Component AnalysisComputers, Materials & Continua, 2023
- CE-Net: Context Encoder Network for 2D Medical Image SegmentationIEEE Transactions on Medical Imaging, 2019
- Non-local Neural Networks2018
- U-Net: Convolutional Networks for Biomedical Image Segmentation2015