원문정보
High-Resolution Remote Sensing Image Scene Classification
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
High-resolution remote sensing image scene classification is a challenging visual task, and this study proposes a remote sensing image scene classification method based on Semantic Multi-Granularity Feature Learning Network (SMGFL-Net). The core idea is to learn global and multi-granularity local features from rearranged intermediate feature mappings, thus eliminating meaningless edges. These features are then fused into the final prediction. Through comparative studies, SMGFL-Net consistently outperforms other peer methods in terms of classification accuracy.
목차
Abstract
1. Introduction
2. This Theory
3. Conclusion
Funding
References
1. Introduction
2. This Theory
3. Conclusion
Funding
References
저자정보
참고문헌
자료제공 : 네이버학술정보