Lane Detection Based on Instance Segmentation of BiSeNet V2 Backbone Network
Most lane line detection algorithms still have room for improvement in detection accuracy, speed, and robustness. Meanwhile, these algorithms only test the performance indicators through the test set of the open-source dataset rather than deploying them on actual vehicles and evaluating the performa...
Main Authors: | Sun Yang, Li Yunpeng, Liu Yu |
---|---|
Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2022-12-01
|
Series: | Applied Artificial Intelligence |
Online Access: | http://dx.doi.org/10.1080/08839514.2022.2085321 |
Similar Items
-
Sea-land Segmentation Method for SAR Images Based on Improved BiSeNet
by: Muchen DAI, et al.
Published: (2020-10-01) -
SA‐BiSeNet: Swap attention bilateral segmentation network for real‐time inland waterways segmentation
by: W.B. Zhang, et al.
Published: (2023-01-01) -
Collaborative Wheat Lodging Segmentation Semi-Supervised Learning Model Based on RSE-BiSeNet Using UAV Imagery
by: Hongbo Zhi, et al.
Published: (2023-11-01) -
A severity estimation method for lightweight cucumber leaf disease based on DM-BiSeNet
by: Kaiyu Li, et al.
Published: (2025-03-01) -
InstLane Dataset and Geometry-Aware Network for Instance Segmentation of Lane Line Detection
by: Qimin Cheng, et al.
Published: (2024-07-01)