The following publications are possibly variants of this publication:
- SPNet: A Spectral Patching Network for End-To-End Hyperspectral Image ClassificationXin Hu, Xinyu Wang 0003, Yanfei Zhong, Ji Zhao 0006, Chang Luo, Lifei Wei. igarss 2019: 963-966 [doi]
- PCCN-MSS: Parallel Convolutional Classification Network Combined Multi-Spatial Scale and Spectral Features for UAV-Borne Hyperspectral With High Spatial Resolution ImageryLinhuan Jiang, Zhen Zhang 0035, Bo-Hui Tang, Lehao Huang, Bingru Zhang. staeors, 17:6529-6543, 2024. [doi]
- Spatial-Spectral Fusion Based on Conditional Random Fields for the Fine Classification of Crops in UAV-Borne Hyperspectral Remote Sensing ImageryLifei Wei, Ming Yu, Yanfei Zhong, Ji Zhao 0006, Yajing Liang, Xin Hu. remotesensing, 11(7):780, 2019. [doi]
- Detecting pine wilt disease at the pixel level from high spatial and spectral resolution UAV-borne imagery in complex forest landscapes using deep one-class classificationJingtao Li, Xinyu Wang 0003, Hengwei Zhao, Xin Hu, Yanfei Zhong. aeog, 112:102947, 2022. [doi]
- What Kind Of Spatial And Spectral Resolution Of Uav-Borne Hyperspectral Image Is Required For Precise Crop Classification When Using Deep LearningBin Yang, Shunshi Hu. whispers 2022: 1-5 [doi]
- SSDC-DenseNet: A Cost-Effective End-to-End Spectral-Spatial Dual-Channel Dense Network for Hyperspectral Image ClassificationYutong Bai, Qifan Zhang, Zexin Lu, Yi Zhang 0018. access, 7:84876-84889, 2019. [doi]
- End-to-End Convolutional Network and Spectral-Spatial Transformer Architecture for Hyperspectral Image ClassificationShiping Li, Lianhui Liang, Shaoquan Zhang, Ying Zhang, Antonio Plaza, Xuehua Wang. remotesensing, 16(2):325, January 2024. [doi]