Adversarial detection based on feature invariant in license plate recognition systems
Deep neural networks have become an integral part of people's daily lives. However, researchers observed that these networks were susceptible to threats from adversarial samples, leading to abnormal behaviors such as misclassification by the network model. The presence of adversarial samples po...
Saved in:
Main Authors: | ZHU Xiaoyu, TANG Peng, ZHANG Haochen, QIU Weidong, HUANG Zheng |
---|---|
Format: | Article |
Language: | English |
Published: |
POSTS&TELECOM PRESS Co., LTD
2024-12-01
|
Series: | 网络与信息安全学报 |
Subjects: | |
Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2024080 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Mape: defending against transferable adversarial attacks using multi-source adversarial perturbations elimination
by: Xinlei Liu, et al.
Published: (2025-01-01) -
Batch-in-Batch: a new adversarial training framework for initial perturbation and sample selection
by: Yinting Wu, et al.
Published: (2025-01-01) -
SURVEY AND PROPOSED METHOD TO DETECT ADVERSARIAL EXAMPLES USING AN ADVERSARIAL RETRAINING MODEL
by: Thanh Son Phan, et al.
Published: (2024-08-01) -
Deep Learning-Based Speech Emotion Recognition Using Multi-Level Fusion of Concurrent Features
by: Samuel, Kakuba, et al.
Published: (2023) -
Licensing of Commensal Rodent Trappers
by: Frederick M. Fishel
Published: (2018-10-01)