Cross-dataset evaluation of visual semantic segmentation models for off-road autonomous driving
Open Access
- 27 April 2026
- journal article
- Published by Elsevier in Expert Systems with Applications
- Vol. 325
Abstract
No abstract availableFunding Information
- Agencia Estatal de Investigación (PLEC2023-010303)
- Agencia Estatal de Investigación (PID2022-136887NB-I00)
- Ministerio de Ciencia, Innovación y Universidades
- Centro para el Desarrollo Tecnológico Industrial
- Comunidad de Madrid (TEC-2024/TEC-62)
- Comunidad de Madrid (iROBOCITY 2030-CM)
This publication has 23 references indexed in Scilit:
- Survey on Unsupervised Domain Adaptation for Semantic Segmentation for Visual Perception in Automated DrivingIEEE Access, 2023
- A Survey of Traversability Estimation for Mobile RobotsIEEE Access, 2022
- A Novel Approach to Cross dataset studies in Facial Expression RecognitionMultimedia Tools and Applications, 2022
- A Deep Learning-Based Hybrid Framework for Object Detection and Recognition in Autonomous DrivingIEEE Access, 2020
- Lidar for Autonomous Driving: The Principles, Challenges, and Trends for Automotive Lidar and Perception SystemsIEEE Signal Processing Magazine, 2020
- RAPNet: Residual Atrous Pyramid Network for Importance-Aware Street Scene ParsingIEEE Transactions on Image Processing, 2020
- Autonomous driving systems hardware and software architecture exploration: optimizing latency and cost under safety constraintsSystems Engineering, 2019
- A survey on deep learning techniques for image and video semantic segmentationApplied Soft Computing, 2018
- Autonomous Off-Road Navigation for MuCAR-3KI - Künstliche Intelligenz, 2011
- The Pascal Visual Object Classes (VOC) ChallengeInternational Journal of Computer Vision, 2009