An Interpretable Compression and Classification System: Theory and Applications

This study proposes a low-complexity interpretable classification system. The proposed system contains main modules including feature extraction, feature reduction, and classification. All of them are linear. Thanks to the linear property, the extracted and reduced features can be inversed to origin...

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Bibliographic Details
Main Authors: Tzu-Wei Tseng, Kai-Jiun Yang, C.-C. Jay Kuo, Shang-Ho Tsai
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9159554/