Nobuyoshi Yabuki
Biographic Data
| ID | 6310141 |
|---|---|
| NAME | Nobuyoshi Yabuki |
| GIVEN NAMES | Nobuyoshi |
| FAMILY NAME | Yabuki |
| SIGNATURE | YABUKI N |
| AFFILIATIONS | The University of Osaka |
| ORCID | 0000-0002-2944-4540 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Benchmarking attention mechanisms and consistency regularization semi-supervised learning for post-flood building damage assessment
Rapid and accurate building damage assessment (BDA) following floods is critical for effective disaster response, yet faces challenges from limited labeled data and subtle damage cues in satellite imagery. Existing deep learning change detection (CD) methods may exhibit low recall or misclassify damage inappropriately when transferred directly to the post-flood BDA (Flood-BDA) task. This study addresses these gaps by establishing the first system…
Integrating GIS, deep learning, and environmental sensors for multicriteria evaluation of urban street walkability
Harnessing multiple data sources and emerging technologies for comprehensive urban green space evaluation
Exploring the association between street built environment and street vitality using deep learning methods
Measuring visual walkability perception using panoramic street view images, virtual reality, and deep learning
Development of a City-Scale Approach for Façade Color Measurement with Building Functional Classification Using Deep Learning and Street View Images
Precise measuring of urban façade color is necessary for urban color planning. The existing manual methods of measuring building façade color are limited by time and labor costs and hardly carried out on a city scale. These methods also make it challenging to identify the role of the building function in controlling and guiding urban color planning. This paper explores a city-scale approach to façade color measurement with building functional cla…
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Development of a City-Scale Approach for Façade Color Measurement with Building Functional Classification Using Deep Learning and Street View Images
Precise measuring of urban façade color is necessary for urban color planning. The existing manual methods of measuring building façade color are limited by time and labor costs and hardly carried out on a city scale. These methods also make it challenging to identify the role of the building function in controlling and guiding urban color planning. This paper explores a city-scale approach to façade color measurement with building functional cla…
Exploring the association between street built environment and street vitality using deep learning methods
Measuring visual walkability perception using panoramic street view images, virtual reality, and deep learning
Integrating GIS, deep learning, and environmental sensors for multicriteria evaluation of urban street walkability
Harnessing multiple data sources and emerging technologies for comprehensive urban green space evaluation
Benchmarking attention mechanisms and consistency regularization semi-supervised learning for post-flood building damage assessment
Rapid and accurate building damage assessment (BDA) following floods is critical for effective disaster response, yet faces challenges from limited labeled data and subtle damage cues in satellite imagery. Existing deep learning change detection (CD) methods may exhibit low recall or misclassify damage inappropriately when transferred directly to the post-flood BDA (Flood-BDA) task. This study addresses these gaps by establishing the first system…
Engineering (6 works) · Computer Science (5 works) · Geography (5 works) · Artificial Intelligence (4 works) · Civil engineering (4 works) · Urban Green Space and Health (4 works) · Built environment (3 works) · Environmental Science (3 works) · Urban Transport and Accessibility (3 works) · Walkability (3 works)