Brain-Inspired Remote Sensing Foundation Models and Open Problems: A Comprehensive Survey

Brain-Inspired Remote Sensing Foundation Models and Open Problems: A Comprehensive Survey

The foundation model (FM) has garnered significant attention for its remarkable transfer performance in downstream tasks. Typically, it undergoes task-agnostic pretraining on a large dataset and can be efficiently adapted to various downstream applications through fine-tuning. While FMs have been ex...

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Bibliographic Details
Main Authors: Licheng Jiao, Zhongjian Huang, Xiaoqiang Lu, Xu Liu, Yuting Yang, Jiaxuan Zhao, Jinyue Zhang, Biao Hou, Shuyuan Yang, Fang Liu, Wenping Ma, Lingling Li, Xiangrong Zhang, Puhua Chen, Zhixi Feng, Xu Tang, Yuwei Guo, Dou Quan, Shuang Wang, Weibin Li, Jing Bai, Yangyang Li, Ronghua Shang, Jie Feng
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Brain modeling
deep learning
foundation model
image analysis
remote sensing
Online Access:https://ieeexplore.ieee.org/document/10254282/

Internet

https://ieeexplore.ieee.org/document/10254282/

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