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第72号 2023年度 VII. 発表業績
第72号 2023年度 VII. 発表業績

著書および学術雑誌等に発表したもの

著書および学術雑誌等に発表したもの

部門・センター：

  • Utilization of Geospatial Information in Daily Life: Expression and Analysis of Dynamic Life Activity:Yoshihide Sekimoto, Yasuhiro Kawahara, Ikuko Yamada, Masahiko Nagai, Toshikazu Seto・1-189, Springer, 2023.5B
  • Automatic Evaluation of Street-Level Walkability Based on Computer Vision Techniques and Urban Big Data:Huang, L., Oki, T., Muto, S., Kim, H., Ogawa, Y. and Sekimoto, Y.・Intelligence for Future Cities, pp.231-259, doi: 10.1007/978-3-031-31746-0_13, 2023.6C
  • WindSR: Improving Spatial Resolution of Satellite Wind Speed Through Super-Resolution:Kumar, A., Islam, T., Ma, J., Kashiyama, T., Sekimoto, Y., & Mattmann, C.・IEEE Access, Vol.11, pp.69486-69494, doi: 10.1109/ACCESS.2023.3292966, 2023.7C
  • Real-time classification of longitudinal conveyor belt cracks with deep-learning approach:Dwivedi, U.; Kumar A.; Sekimoto, Y.・PLOS ONE, Vol.18 No.7, pp.0284788, doi: 10.1371/journal.pone.0284788, 2023.7C
  • Quantitative land price analysis via computer vision from street view images:Zhao, C., Ogawa, Y., Chen, S., Oki, T., Sekimoto, Y.・Engineering Applications of Artificial Intelligence, Vol.123, pp.106294, doi: 10.1016/j.engappai.2023.106294, 2023.8C
  • Social segregation levels vary depending on activity space types: Comparison of segregation in residential, workplace, routine and non-routine activities in Tokyo metropolitan area:Sun, C., Shibuya, Y., and Sekimoto, Y.・Cities, Vol.146, doi: 10.1016/j.cities.2023.104745, 2023.12C
  • Enhancing Geospatial Retail Analysis By Integrating Synthetic Human Mobility Simulations:Garcia-Gabilondo, S., Shibuya, Y., Sekimoto, Y.・Computers, Environment and Urban Systems, Vol.108, doi: 10.1016/j.compenvurbsys.2023.102058, 2023.12C
  • Generating Diverse Optimal Road Management Plans in Post-Disaster by Applying Envelope Multi-Objective Deep Reinforcement Learning:Joo, S.H., Ogawa, Y. and Sekimoto, Y.・Journal of Disaster Research, Vol.18 No.8, pp.884-894, doi: 10.20965/jdr.2023.p0884, 2023.12C
  • Geometric-based approach for linking various building measurement data to a 3D city model:Ogawa, Y., Sato, G. and Sekimoto, Y.・PLoS ONE, Vol.19 No.1, doi: 10.1371/journal.pone.0296445, 2024.1C
  • From global challenges to local solutions: A review of cross-country collaborations and winning strategies in road damage detection:Arya, D., Maeda, H., and Sekimoto, Y.・Advanced Engineering Informatics, Vol.60, pp.102388, doi: 10.1016/j.aei.2024.102388, 2024.3C
  • Federated learning-based global road damage detection:Saha, P.K., Arya, D., and Sekimoto, Y.・Computer-Aided Civil and Infrastructure Engineering, pp.45307, doi: 10.1111/mice.13186, 2024.3C
  • Evaluating the subjective perceptions of streetscapes using street-view images:Ogawa, Y., Oki, T., Zhao, C., Sekimoto Y., Shimizu, C.・Landscape and Urban Planning, Vol.247, pp.105073, doi: 10.1016/j.landurbplan.2024.105073, 2024.3C
  • Realtime damage detection in long conveyor belts using deep learning approach:Dwivedi, U., Kumar, A.; Sekimoto, Y.・The International Association for Automation and Robotics in Construction, India (IIT Madras), [2023 Proceedings of the 40th ISARC, Chennai, India, 2023.7], 2023.7D
  • Are utility poles within sight? Unleashing the power of vision for effortless roadside:Zhehui, Y., Arya, D., Zhao, C., Maeda, H., Sekimoto, Y.・IEEE International Conference on Intelligent Transportation Systems ITSC 2023, Spain, [IEEE ITSC-2023, 2024.2], 2023.9D
  • Deep Learning Approach to Logistics Trips Generation: Enhancing Pseudo People Flow with Agent-based Modeling:Zhang, K., Pang, Y., and Sekimoto, Y.・IEEE ITSC-2023, Spain, [IEEE ITSC-2023, 2024.2], 2023.9D
  • Unmasking Socioeconomic Disparities: A Study of Urban Segregation through the Lens of Mobile App Usage Patterns:Shibuya, Y., Garcia, S., Chenchen, S., Peiran, Y., Jue, M., Sekimoto, Y.・Netmob 2023, Spain, [NetMob 2023 Book of Abstracts, 2023.10], 2023.10D
  • Label Freedom: Stable Diffusion for Remote Sensing Image Semantic Segmentation Data Generation:Zhao, C., Ogawa, Y., Chen, S., Yang, Z., Sekimoto, Y.・IEEE BigData 2023, Sorrento, Italy, [IEEE BigData 2023, 2023.12], 2023.12D
  • Unveiling the Road Matrix: Development of Versatile Pavement Surface Models from Low-resolution Aerial Images:Liao, L., Arya, D., and Sekimoto, Y.・2023 IEEE International Conference on Big Data, Sorrento, Italy, [Big Data Learning and Analytics, 2023.12], 2023.12D
  • Advancing Building Extraction in Thailand using the YOLOv8 Segment Model on Open- source Data across Diverse Land-Use-Types:Chintakindi, B., Ogawa Y., and Sekimoto Y.・The 32nd Annual Conference of Geographic Information System Association (GISA) and International Association of Geo-informatics (IAG'i) 2023, Japan, ［Proceedings of the 32nd Geographic Information Systems Association Academic Research Presentation Conference, 2023.10］, 2023.10E
  • Mapping Emotional Geographical Trends and User Behaviors Based on Japanese Tweets: A Case Study of Urban Green Spaces in Tokyo 23 Wards:Liu, M., Shibuya, Y., Sekimoto, Y.・The 32nd Annual Conference of Geographic Information System Association (GISA) and International Association of Geo-informatics (IAG'i) 2023, 東京, ［第32回地理情報システム学会学術研究発表大会講演論文集, 2023.10］, 2023.10E
  • Towards Pseudo People Flow: Developing a Deep Generative Model based on PT Data to Reproduce Large-Scale Daily People Activity Profiles:Yurong ZHANG, Kunyi ZHANG, Yanbo PANG, Yoshihide SEKIMOTO・The 32nd Annual Conference of Geographic Information System Association (GISA) and International Association of Geo-informatics (IAG'i) 2023, 東京, ［第32回地理情報システム学会学術研究発表大会講演論文集, 2023.10］, 2023.10E
  • Evaluating the Economic Consequences of COVID-19: A Comprehensive Study Utilizing Probe Vehicle Data and POI Data:Tang, G., Ogawa, Y., and Zhao, C., Sekimoto, Y.・The International Association of Geo-informatics (IAG'i) Conference 2023, Japan, ［Proceedings, 2023.10］, 2023.10E
  • Evaluation Method for Large-scale Building Footprint Extraction: A Two-level Approach Using Proxy Data and Building Matching:陳聖隆, 小川芳樹, 関本義秀・第32回地理情報システム学会学術研究発表大会, 東京, ［第32回地理情報システム学会学術研究発表大会講演論文集, 2023.10］, 2023.10E
  • Reducing annotation effort in footprint extraction: An innovative weakly supervised framework leveraging open source data:陳聖隆, 小川芳樹, 関本義秀・CSIS Days 2023, 2023.11E
  • 緊急提言　デジタル化が導く「未来」　名古屋工業大学　秀島栄三教授に聞く　多様なサービスを生み出す源泉に　BIM/CIMと組み合わせ可能性拡大:建設通信新聞（朝刊）3面, 2023.5.25G
  • デジタル南砺の協議会が初会合:富山新聞（朝刊）23面, 2023.7.1G
  • 建物に関する様々な計測データの3D都市モデルへの効率的なマッチング:佐藤剛・ESTRELA 7月号, 2023.7.10G
  • デジタル社会における地域での市民協働の未来像:関本義秀・ていくおふ, 2023.9.6G
  • イノベーション　東京大学　空間情報科学研究センター　関本義秀教授　初の道路損傷データセット公開:日刊建設工業新聞（別冊）（朝刊）18面, 2023.12.13G
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