AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
How to
Here you can find the complete list of our publications.
You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2025
Wan, X.; Luo, Y.
A Study of Anti-war Memorial Hall of Leshan City based on Virtual Museum Technology Proceedings Article
In: pp. 493–497, Association for Computing Machinery, Inc, 2025, ISBN: 9798400712432 (ISBN).
Abstract | Links | BibTeX | Tags: 3d modeling technologies, 3D reconstruction, Anti-war, Artificial intelligence, Augmented Reality, Digital researches, Historic Preservation, Human engineering, Interactive computer graphics, Knowledge graph, Knowledge graphs, Language Model, Localization and mappings, Metaverses, Model knowledge, Museum technology, Museums, Restoration, Three dimensional computer graphics, Virtual museum, Virtual Reality
@inproceedings{wan_study_2025,
title = {A Study of Anti-war Memorial Hall of Leshan City based on Virtual Museum Technology},
author = {X. Wan and Y. Luo},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105011594066&doi=10.1145%2F3732801.3732887&partnerID=40&md5=ac25032b46edf5a9d5949b8ceb5a41e1},
doi = {10.1145/3732801.3732887},
isbn = {9798400712432 (ISBN)},
year = {2025},
date = {2025-01-01},
pages = {493–497},
publisher = {Association for Computing Machinery, Inc},
abstract = {This study adopted augmented reality (AR), virtual reality (VR), artificial intelligence (AI), metaverse (META), large language models (LLM), knowledge graphs (KG), and synchronous localization and mapping (SLAM) technologies to create a virtual museum (VM) with the theme of the history of Leshan anti-Japanese war. Its aim is to enrich the digital research of this area, and to restore and vividly reflect the significance of Leshan’s contributions during the anti-Japanese war. This study combines 3D modeling technology with historical scene restoration to create a method of field investigation of local history and anti-Japanese war sites, which constructed six unique exhibition areas to describe historical events. The virtual museum integrates lots of historical sites, stories, achievements, and cultural aspects into a unique cultural interaction center. Through diverse technological approaches, this study aims to enable the public to contemplate history, cultivate national pride and patriotism, and deliver novel strategies for the digital protection of historical heritage. © 2025 Elsevier B.V., All rights reserved.},
keywords = {3d modeling technologies, 3D reconstruction, Anti-war, Artificial intelligence, Augmented Reality, Digital researches, Historic Preservation, Human engineering, Interactive computer graphics, Knowledge graph, Knowledge graphs, Language Model, Localization and mappings, Metaverses, Model knowledge, Museum technology, Museums, Restoration, Three dimensional computer graphics, Virtual museum, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
This study adopted augmented reality (AR), virtual reality (VR), artificial intelligence (AI), metaverse (META), large language models (LLM), knowledge graphs (KG), and synchronous localization and mapping (SLAM) technologies to create a virtual museum (VM) with the theme of the history of Leshan anti-Japanese war. Its aim is to enrich the digital research of this area, and to restore and vividly reflect the significance of Leshan’s contributions during the anti-Japanese war. This study combines 3D modeling technology with historical scene restoration to create a method of field investigation of local history and anti-Japanese war sites, which constructed six unique exhibition areas to describe historical events. The virtual museum integrates lots of historical sites, stories, achievements, and cultural aspects into a unique cultural interaction center. Through diverse technological approaches, this study aims to enable the public to contemplate history, cultivate national pride and patriotism, and deliver novel strategies for the digital protection of historical heritage. © 2025 Elsevier B.V., All rights reserved.
2024
Wu, J.; Gan, W.; Chao, H. -C.; Yu, P. S.
Geospatial Big Data: Survey and Challenges Journal Article
In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 17007–17020, 2024, ISSN: 21511535 (ISSN); 19391404 (ISSN), (Publisher: Institute of Electrical and Electronics Engineers Inc.).
Abstract | Links | BibTeX | Tags: Artificial intelligence, artificial intelligence (AI), Behavioral Research, Big Data, Data challenges, Data Mining, Data surveys, Data visualization, Earth observation data, Environmental management, environmental protection, Geo-spatial, Geo-spatial analysis, Geo-spatial data, Geospatial big data, geospatial big data (GBD), geospatial data, GIS, Green products, Human behaviors, Knowledge graph, Knowledge graphs, satellite, sensor, spatial data, Sustainable development, urban planning
@article{wu_geospatial_2024,
title = {Geospatial Big Data: Survey and Challenges},
author = {J. Wu and W. Gan and H. -C. Chao and P. S. Yu},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200804056&doi=10.1109%2FJSTARS.2024.3438376&partnerID=40&md5=63c39a7c302e6d9ff055633efab0349a},
doi = {10.1109/JSTARS.2024.3438376},
issn = {21511535 (ISSN); 19391404 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
volume = {17},
pages = {17007–17020},
abstract = {In recent years, geospatial big data (GBD) has obtained attention across various disciplines, categorized into big Earth observation data and big human behavior data. Identifying geospatial patterns from GBD has been a vital research focus in the fields of urban management and environmental sustainability. This article reviews the evolution of GBD mining and its integration with advanced artificial intelligence techniques. GBD consists of data generated by satellites, sensors, mobile devices, and geographical information systems, and we categorize geospatial data based on different perspectives. We outline the process of GBD mining and demonstrate how it can be incorporated into a unified framework. In addition, we explore new technologies, such as large language models, the metaverse, and knowledge graphs, and how they could make GBD even more useful. We also share examples of GBD helping with city management and protecting the environment. Finally, we discuss the real challenges that come up when working with GBD, such as issues with data retrieval and security. Our goal is to give readers a clear view of where GBD mining stands today and where it might go next. © 2024 Elsevier B.V., All rights reserved.},
note = {Publisher: Institute of Electrical and Electronics Engineers Inc.},
keywords = {Artificial intelligence, artificial intelligence (AI), Behavioral Research, Big Data, Data challenges, Data Mining, Data surveys, Data visualization, Earth observation data, Environmental management, environmental protection, Geo-spatial, Geo-spatial analysis, Geo-spatial data, Geospatial big data, geospatial big data (GBD), geospatial data, GIS, Green products, Human behaviors, Knowledge graph, Knowledge graphs, satellite, sensor, spatial data, Sustainable development, urban planning},
pubstate = {published},
tppubtype = {article}
}
In recent years, geospatial big data (GBD) has obtained attention across various disciplines, categorized into big Earth observation data and big human behavior data. Identifying geospatial patterns from GBD has been a vital research focus in the fields of urban management and environmental sustainability. This article reviews the evolution of GBD mining and its integration with advanced artificial intelligence techniques. GBD consists of data generated by satellites, sensors, mobile devices, and geographical information systems, and we categorize geospatial data based on different perspectives. We outline the process of GBD mining and demonstrate how it can be incorporated into a unified framework. In addition, we explore new technologies, such as large language models, the metaverse, and knowledge graphs, and how they could make GBD even more useful. We also share examples of GBD helping with city management and protecting the environment. Finally, we discuss the real challenges that come up when working with GBD, such as issues with data retrieval and security. Our goal is to give readers a clear view of where GBD mining stands today and where it might go next. © 2024 Elsevier B.V., All rights reserved.