23 citations · 36 across the 4 of their papers we have counts for
4 papers
Single-Shot Global Localization via Graph-Theoretic Correspondence Matching
Shigemichi Matsuzaki, Kenji Koide, Shuji Oishi +2
This paper describes a method of global localization based on graph-theoretic association of instances between a query and the prior map. The proposed framework employs corresponde…
Multi-Source Soft Pseudo-Label Learning with Domain Similarity-based Weighting for Semantic Segmentation
Shigemichi Matsuzaki, Hiroaki Masuzawa, Jun Miura
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 propo…
Image-based scene recognition for robot navigation considering traversable plants and its manual annotation-free training
Shigemichi Matsuzaki, Hiroaki Masuzawa, Jun Miura
This paper describes a method of estimating the traversability of plant parts covering a path and navigating through them for mobile robots operating in plant-rich environments. Co…
Multi-source Pseudo-label Learning of Semantic Segmentation for the Scene Recognition of Agricultural Mobile Robots
Shigemichi Matsuzaki, Jun Miura, Hiroaki Masuzawa
This paper describes a novel method of training a semantic segmentation model for scene recognition of agricultural mobile robots exploiting publicly available datasets of outdoor…