Chat-RSC: interactive remote sensing image classification via large language models
Large language models (LLMs) have demonstrated remarkable collaboration and interaction capabilities across numerous work domains. Therefore, could LLMs also contribute to remote sensing classification and interpretation, which are among the most fundamental tasks in the field of remote sensing? To...
Saved in:
| Main Authors: | Xin Pan, Xiangfei She, Xiaofeng Li, Jian Zhao |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-08-01
|
| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2519999 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Evaluation of deepseek, gemini, ChatGPT-4o, and perplexity in responding to salivary gland cancer
by: Ahmed Bashah, et al.
Published: (2025-08-01) -
Rooted in and beyond interaction: A systematic review of interactive affordances of chatbots for language learning amidst the rise of large language models
by: Yunfei Du, et al.
Published: (2025-09-01) -
S<sup>2</sup>RCFormer: Spatial-Spectral Residual Cross-Attention Transformer for Multimodal Remote Sensing Data Classification
by: Yifei Xu, et al.
Published: (2025-01-01) -
Dynamic convolutional model based on distribution-collaboration strategy for remote sensing scene classification
by: Chenjun Xu, et al.
Published: (2025-08-01) -
VSEST 29110 Tool: Using ChatGPT to Evaluate the Implementation of the ISO/IEC 29110 Work Products
by: Jezreel Mejia, et al.
Published: (2024-01-01)