Template Matching Based on Geometric Invariance in Deep Neural Network

Template Matching Based on Geometric Invariance in Deep Neural Network

Machine learning models, especially deep neural networks (DNNs), have achieved state of the art in computer vision and speech recognition. However, with wide applications of DNNs, some problems have appeared, such as lack of interpretability and vulnerable to adversarial examples. Whether the judgme...

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Bibliographic Details
Main Authors: Yaming Cao, Zhen Yang, Haijiao Wang, Xiaodong Peng, Chen Gao, Yun Li
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Deep neural network
geometric invariant
interpretability
template match
adversarial example
Online Access:https://ieeexplore.ieee.org/document/8740853/

Internet

https://ieeexplore.ieee.org/document/8740853/

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