An improved DeepLabv3 + railway track extraction algorithm based on densely connected and attention mechanisms
Abstract The railway track extraction using unmanned aerial vehicle (UAV) aerial images suffers from issues such as low extraction accuracy and high time consumption. In response to these problems, this paper presents a lightweight algorithm DA-DeepLabv3 + based on densely connected and attention me...
Saved in:
Main Authors: | Yanbin Weng, Jie Yang, Changfan Zhang, Jing He, Cheng Peng, Lin Jia, Hui Xiang |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-024-84937-5 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multiscale guided attention network for optic disc segmentation of retinal images
by: A Z M Ehtesham Chowdhury, et al.
Published: (2025-01-01) -
SSMM-DS: A semantic segmentation model for mangroves based on Deeplabv3+ with swin transformer
by: Zhenhua Wang, et al.
Published: (2024-10-01) -
LEAF-YOLO: Lightweight Edge-Real-Time Small Object Detection on Aerial Imagery
by: Van Quang Nghiem, et al.
Published: (2025-03-01) -
DPD-YOLO: dense pineapple fruit target detection algorithm in complex environments based on YOLOv8 combined with attention mechanism
by: Cong Lin, et al.
Published: (2025-01-01) -
Improving UAV Aerial Imagery Detection Method via Superresolution Synergy
by: Dianwei Wang, et al.
Published: (2025-01-01)