How Semantic Segmentation works part3(Machine Learning)
1. Multi-Source Soft Pseudo-Label Learning with Domain Similarity-based Weighting for SemanticSegmentation(arXiv) Author : Shigemichi Matsuzaki, Hiroaki Masuzawa, Jun Miura Abstract : This paper describes a method of domain adaptive training for semantic segmentation using multiple source datasets that are not necessarily relevant to the target dataset. We propose a soft…
How Semantic Segmentation works part3(Machine Learning) 1. Multi-Source Soft Pseudo-Label Learning with Domain Similarity-based Weighting for SemanticSegmentation(arXiv) Author : Shigemichi Matsuzaki, Hiroaki Masuzawa, Jun Miura Abstract : This paper describes a method of domain adaptive training for semantic segmentation using multiple source datasets that are not necessarily relevant to the target dataset. We propose a soft… deep-learning
Semantic Segmentation work part3Machine Learning 1 MultiSource Soft PseudoLabel Learning Domain Similaritybased Weighting SemanticSegmentationarXiv Author Shigemichi Matsuzaki Hiroaki Masuzawa Jun Miura Abstract paper describes method domain adaptive training semantic segmentation using multiple source datasets necessarily relevant target dataset propose soft… deeplearning