农业遥感图像分类方法、装置、设备及介质
By combining 3D-CNN and VIT models, and utilizing the data interaction module and Coordinate Attention mechanism, the problem of fusing local features and contextual information in hyperspectral images was solved, achieving high-precision agricultural remote sensing image classification and supporting the development of smart agriculture.
CN117649561BActive Publication Date: 2026-07-17SOUTH CHINA AGRICULTURAL UNIVERSITY
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SOUTH CHINA AGRICULTURAL UNIVERSITY
- Filing Date
- 2023-12-21
- Publication Date
- 2026-07-17
Smart Images
Figure CN117649561B_ABST
Abstract
本申请涉及一种农业遥感图像分类方法、装置、设备及介质，所述方法包括：由3D‑CNN模型以及VI T模型构建农业遥感图像分类模型，通过3D‑CNN模型捕获光谱维度信息，传递给VI T模型，利用VI T模型全局感知的特点将信息传递给3D‑CNN模型，能够使两个模型全面地提取光谱特征和全局信息，达到相辅相成的效果，有效改善高光谱图像识别任务的性能，并获得更高的分类精确度。本申请能够在复杂的农业环境下对农业遥感图像进行分类，进一步推动智慧农业的发展，为自动化农业打下坚实的理论基础。
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