Work

Unsupervised Spatial–Spectral Feature Learning by 3D Convolutional Autoencoder for Hyperspectral Classification

Year: 2019

Type: article

Source: IEEE Transactions on Geoscience and Remote Sensing

DOI: 10.1109/tgrs.2019.2908756

Authors: Shaohui Mei, Jingyu Ji, Yunhao Geng, Zhi Zhang, Xu Li, Qian Du

Institutions: Northwestern Polytechnical University, Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, State Key Laboratory of Remote Sensing Science, Mississippi State University

Language: English

Topic: Remote-Sensing Image Classification

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

Open Access status: closed

Funders: National Natural Science Foundation of China, China Postdoctoral Science Foundation, Natural Science Foundation of Shaanxi Province, Fundamental Research Funds for the Central Universities

Awards: G470046289, 基于稀疏低秩表示与深度学习理论的高光谱图像光谱变化处理研究, G5208857031, G7384725169, G7815016644

OpenAlex ID: W2940678725

FWCI: 24.74

Cites: 58

Cited by: 317

Related to: 10