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
-
Double adversarial attack against license plate recognition system
by: Xianyi CHEN, et al.
Published: (2023-06-01) -
MLPR: YOLOv3 for Real-Time License Plate Recognition in Moroccan Video Streams
by: Hatim Derrouz, et al.
Published: (2025-01-01) -
Cloud-Based License Plate Recognition: A Comparative Approach Using You Only Look Once Versions 5, 7, 8, and 9 Object Detection
by: Christine Bukola Asaju, et al.
Published: (2025-01-01) -
PURP: A Scalable System for Predicting Short-Term Urban TrafficFlow Based on License Plate Recognition Data
by: Shan Zhang, et al.
Published: (2024-03-01) -
Adversarial examples detection method based on boundary values invariants
by: Fei YAN, et al.
Published: (2020-02-01)