Prototype Guided Pseudo Labeling and Perturbation-based Active Learning for domain adaptive semantic segmentation-Reference-Cited by-同舟云学术

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Prototype Guided Pseudo Labeling and Perturbation-based Active Learning for domain adaptive semantic segmentation

Published:2024-04 Issue: Volume:148 Page:110203
ISSN:0031-3203
Container-title:Pattern Recognition
language:en
Short-container-title:Pattern Recognition

Author:

Peng Junkun^ORCID,Sun Mingjie,Lim Eng Gee^ORCID,Wang Qiufeng,Xiao Jimin

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference61 articles.

1. Multinet: Real-time joint semantic reasoning for autonomous driving;Teichmann,2018

2. Denseaspp for semantic segmentation in street scenes;Yang,2018

3. Progressive sample mining and representation learning for one-shot person re-identification;Li;Pattern Recognit.,2021

4. Adapnet: Adaptive semantic segmentation in adverse environmental conditions;Valada,2017

5. Gradient and log-based active learning for semantic segmentation of crop and weed for agricultural robots;Sheikh,2020

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