Accuracy Improvement of Semantic Segmentation Trained with Data Generated from a 3D Model by Histogram Matching Using Suitable References. - Miho Adachi; Hayato Komatsuzaki; Marin Wada; Ryusuke Miyamoto (SMC, 2022)

Effect of Varied Datasets on Training of a Segmentation Model Used in Visual Navigation. - Marin Wada; Miho Adachi; Ryusuke Miyamoto (IEEE Big Data, 2023)

Does a Dense Point Cloud for Training Data Generation Improve Segmentation Accuracy? - Marin Wada; Hiroaki Sudo; Miho Adachi; Ryusuke Miyamoto (IEEE Big Data, 2023)

Improvement of Visual Odometry Based on Robust Feature Extraction Considering Semantics. - Miho Adachi; Junfeng Xue; Kazufumi Honda; Marin Wada; Ryusuke Miyamoto (CoDIT, 2023)

Dataset Genreratoin for Semantic Segmentation from 3D Scanned Data Considering Domain Gap. - Marin Wada; Miho Adachi; Yuriko Ueda; Ryusuke Miyamoto (CoDIT, 2023)

Dataset Creation for Segmentation to Enhance Visual Navigation in a Targeted Indoor Environment. - Yuriko Ueda; Marin Wada; Miho Adachi; Ryusuke Miyamoto (SITIS, 2023)

Practical Implementation of Visual Navigation Based on Semantic Segmentation for Human-Centric Environments. - Miho Adachi; Kazufumi Honda; Junfeng Xue; Hiroaki Sudo; Yuriko Ueda; Yuki Yuda; Marin Wada; Ryusuke Miyamoto (J. Robotics Mechatronics, 2023)

Data Augmentation for Semantic Segmentation Using a Real Image Dataset Captured Around the Tsukuba City Hall. - Yuriko Ueda; Miho Adachi; Junya Morioka; Marin Wada; Ryusuke Miyamoto (J. Robotics Mechatronics, 2023)

Dataset Creation for Semantic Segmentation Using Colored Point Clouds Considering Shadows on Traversable Area. - Marin Wada; Yuriko Ueda; Junya Morioka; Miho Adachi; Ryusuke Miyamoto (J. Robotics Mechatronics, 2023)

Area-wise Augmentation on Segmentation Datasets from 3D Scanned Data Used for Visual Navigation. - Marin Wada; Yuriko Ueda; Miho Adachi; Ryusuke Miyamoto (CoDIT, 2024)

Effect of Human-Selected Hard Examples to Improve Accuracy of Semantic Segmentation. - Yuriko Ueda; Marin Wada; Miho Adachi; Ryusuke Miyamoto (DSN-S, 2025)