Bibliographic Details
| Title: |
Research on the Spatial Data Intelligent Foundation Model |
| Authors: |
Wang, Shaohua, Xie, Xing, Li, Yong, Guo, Danhuai, Cai, Zhi, Liu, Yu, Yue, Yang, Pan, Xiao, Lu, Feng, Wu, Huayi, Gui, Zhipeng, Ding, Zhiming, Zheng, Bolong, Zhang, Fuzheng, Wang, Jingyuan, Chen, Zhengchao, Lu, Hao, Li, Jiayi, Yue, Peng, Yu, Wenhao, Yao, Yao, Sun, Leilei, Zhang, Yong, Chen, Longbiao, Du, Xiaoping, Li, Xiang, Zhang, Xueying, Qin, Kun, Gong, Zhaoya, Dong, Weihua, Meng, Xiaofeng |
| Publication Year: |
2024 |
| Collection: |
Computer Science |
| Subject Terms: |
Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning |
| More Details: |
This report focuses on spatial data intelligent large models, delving into the principles, methods, and cutting-edge applications of these models. It provides an in-depth discussion on the definition, development history, current status, and trends of spatial data intelligent large models, as well as the challenges they face. The report systematically elucidates the key technologies of spatial data intelligent large models and their applications in urban environments, aerospace remote sensing, geography, transportation, and other scenarios. Additionally, it summarizes the latest application cases of spatial data intelligent large models in themes such as urban development, multimodal systems, remote sensing, smart transportation, and resource environments. Finally, the report concludes with an overview and outlook on the development prospects of spatial data intelligent large models.
Comment: V1 and V2 are in Chinese language, other versions are in English |
| Document Type: |
Working Paper |
| Language: |
English |
| Access URL: |
http://arxiv.org/abs/2405.19730 |
| Accession Number: |
edsarx.2405.19730 |
| Database: |
arXiv |
