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IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium by Chen, Xiaoying (author);Wang, Xiuxiu (author);Guo, Chubing (author);Chen, Chao (author);Gou, Shuiping (author);Yu, Tao (author);Jiao, Changzhe (author) is a nonfiction available to read on EtoBox.
What is IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium about?
Modeling target detection problem given inaccurate annotations as a multiple instance learning (MIL) problem is an effective way for addressing the ground truth uncertainties of remotely sensed hyperspectral imagery. In this paper, we propose a hyperspectral target detection method based on 1D convolution neural network (1DCNN) feature extraction and long short term memory network (LSTM) under the MIL framework, where the LSTM features for each hyperspectral pixel is further refined by a scoring network as to discriminate the real target instance from the inaccurately labeled hyperspectral regions. The proposed method has achieved superior results on both simulated data and real hyperspectral data over the state-ofthe-art methods, showing the prospects for further investigation.
Who reads IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Chen, Xiaoying (author);Wang, Xiuxiu (author);Guo, Chubing (author);Chen, Chao (author);Gou, Shuiping (author);Yu, Tao (author);Jiao, Changzhe (author)
- Publisher
- IEEE
- Published
- 2020
- Language
- DA
- Category
- nonfiction