Institutional Repository of Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Hyperspectral and lidar data land-use classification using parallel transformers | |
Yuxuan, Hu1,2![]() ![]() ![]() | |
2022-07 | |
Conference Name | IEEE International Geoscience and Remote Sensing Symposium |
Conference Date | 2022-7-17 -> 2022-7-22 |
Conference Place | 线上会议 |
Abstract | It has been proved that the fusion of hyperspectral and LiDAR data can effectively improve the performance of land-use classification. Hyperspectral data contain more information than LiDAR data but most recent models pay more attention to the design of feature fusion mechanisms. They use CNN which is not powerful enough in extracting spatialspectral features of hyperspectral data. In this paper, a simple yet effective model with parallel transformers is proposed. Transformer is a powerful tool for both feature extraction and feature fusion. One transformer acts as an hyperspectral image feature extractor while the other transformer is responsible for capturing crossmodal interactions. Experiments on Houston dataset and MUUFL Gulfport dataset demonstrate that the proposed model has significantly better performance than other state-of-the-art models. |
Keyword | Hyperspectral LiDAR Data Fusion Transformer Crossmodal |
Indexed By | EI |
Document Type | 会议论文 |
Identifier | http://ir.ia.ac.cn/handle/173211/48691 |
Collection | 模式识别国家重点实验室_先进时空数据分析与学习 |
Corresponding Author | Lubin, Weng |
Affiliation | 1.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 2.School of Artificial Intelligence, University of Chinese Academy of Sciences |
First Author Affilication | Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
Corresponding Author Affilication | Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
Recommended Citation GB/T 7714 | Yuxuan, Hu,Hao, He,Lubin, Weng. Hyperspectral and lidar data land-use classification using parallel transformers[C],2022. |
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Hyperspectral and li(1565KB) | 会议论文 | 开放获取 | CC BY-NC-SA | View Download |
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