CTFN: Multi-scale CNN and transformer with graph encodings fusion network for hyperspectral image classification

Author:

Yang Aitao,Li MinORCID,Ding YaoORCID,He Yujie,Bi Meiqiao,Zheng Qinghe

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference46 articles.

1. Object-based classification of hyperspectral data using random forest algorithm;Amini;Geo-Spatial Information Science,2018

2. 3-D deep learning approach for remote sensing image classification;Ben Hamida;IEEE Transactions on Geoscience and Remote Sensing,2018

3. Multiscale graph sample and aggregate network with context-aware learning for hyperspectral image classification;Ding;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2021

4. Weighted feature fusion of convolutional neural network and graph attention network for hyperspectral image classification;Dong;IEEE Transactions on Image Processing,2022

5. An image is worth 16x16 words: Transformers for image recognition at scale;Dosovitskiy;Proceedings of the AAAI Conference on Artificial Intelligence,2020

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