An Efficient Data Augmentation Network for Out-of-Distribution Image Detection

An Efficient Data Augmentation Network for Out-of-Distribution Image Detection

Since deep neural networks may classify out-of-distribution image data into in-distribution classes with high confidence scores, this problem may cause serious or even fatal hazards in certain applications, such as autonomous vehicles and medical diagnosis. Therefore, out-of-distribution detection (...

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Bibliographic Details
Main Authors: Cheng-Hung Lin, Cheng-Shian Lin, Po-Yung Chou, Chen-Chien Hsu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Out-of-distribution detection
image classification
anomaly detection
outlier detection
data augmentation
deep neural networks
Online Access:https://ieeexplore.ieee.org/document/9363111/

Internet

https://ieeexplore.ieee.org/document/9363111/

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