The model divides an image into blocks and encodes the position so that the image is transformed into the embedding vector that can be input into the transformer encoder while adding the cls embedding to the input to achieve the effect of image classification.
Abstract. Crop classification of large-scale agricultural land is crucial for crop monitoring and yield estimation. Hyperspectral image classification has ...
Dec 17, 2023 · Crop classification of large-scale agricultural land is crucial for crop monitoring and yield estimation. Hyperspectral image classification ...
A Transformer-Based End-to-End Hyperspectral Image Classification ...
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Apr 21, 2023 · This paper analyzes the methods based on semantic segmentation and proposes a Transformer-based method called HyperSFormer for crop ...
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HyperSFormer: A Transformer-Based End-to-End Hyperspectral Image Classification Method for Crop Classification. J. Xie, J. Hua, S. Chen, P. Wu, P. Gao, D ...
The study introduces a dandelion optimizer with deep transfer learning-based crop type detection and classification (DODTL-CTDC) technique on HSI. The DODTL- ...
HyperSFormer: A Transformer-Based End-to-End Hyperspectral Image Classification Method for Crop Classification. Remote Sens. 2023, 15, 3491. https://doi.org ...
May 2, 2024 · Lu, “Hypersformer: A transformer-based end-to-end hyperspectral image classification method for crop classification,” Remote Sensing, vol.
HyperSFormer: A Transformer-Based End-to-End Hyperspectral Image Classification Method for Crop Classification · Computer Science, Agricultural and Food Sciences.
Nov 10, 2023 · Lu, ''HyperSFormer: A transformer-based end-to-end hyperspectral image classification method for crop classification,'' Remote Sens., vol ...