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Hong, Danfeng (2019) Regression-Induced Representation Learning and Its Optimizer: A Novel Paradigm to Revisit Hyperspectral Imagery Analysis. Dissertation, Technical University of Munich.
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Official URL: https://mediatum.ub.tum.de/?id=1485285
| Item URL in elib: | https://elib.dlr.de/134452/ | ||||||||
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| Document Type: | Thesis (Dissertation) | ||||||||
| Title: | Regression-Induced Representation Learning and Its Optimizer: A Novel Paradigm to Revisit Hyperspectral Imagery Analysis | ||||||||
| Authors: |
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| Date: | 2019 | ||||||||
| Refereed publication: | No | ||||||||
| Open Access: | Yes | ||||||||
| Number of Pages: | 211 | ||||||||
| Status: | Published | ||||||||
| Keywords: | hyperspectral remote sensing, dimensionality reduction, spectral unmixing, multimodal data analysis, machine learning, regression, optimization | ||||||||
| Institution: | Technical University of Munich | ||||||||
| Department: | Department of Civil, Geo and Environmental Engineering | ||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||
| HGF - Program: | Space | ||||||||
| HGF - Program Themes: | Earth Observation | ||||||||
| DLR - Research area: | Raumfahrt | ||||||||
| DLR - Program: | R EO - Earth Observation | ||||||||
| DLR - Research theme (Project): | R - Vorhaben hochauflösende Fernerkundungsverfahren (old) | ||||||||
| Location: | Oberpfaffenhofen | ||||||||
| Institutes and Institutions: | Remote Sensing Technology Institute > EO Data Science | ||||||||
| Deposited By: | Yao, Jing | ||||||||
| Deposited On: | 19 Mar 2020 08:26 | ||||||||
| Last Modified: | 01 Apr 2020 10:39 |
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