A system for identifying an anti-counterfeiting pattern based on the statistical difference in key image regions-Reference-Cited by-同舟云学术

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A system for identifying an anti-counterfeiting pattern based on the statistical difference in key image regions

Published:2021-11 Issue: Volume:183 Page:115410
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Zheng Zhaohui,Zheng Hong,Ju Jianping,Chen Deng,Li Xi,Guo Zhongyuan,You Changhui,Lin Mingyu

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference32 articles.

1. Managing computational complexity using surrogate models: a critical review;Alizadeh;Research in Engineering Design,2020

2. Biomimetic micro fingerprints for anti-counterfeiting strategies;Bae;Advanced Materials,2015

3. Automatic identification algorithm of texture anti-counterfeiting tag base on transform domain;Cheng,2015

4. Repulsive-and-attractive local binary gradient contours: new and efficient feature descriptors for texture classification;El Khadiri;Information Sciences,2018

5. Elkasrawi, S., & Shafait, F. (2014). Printer identification using supervised learning for document forgery detection. The 11th IAPR International Workshop on Document Analysis Systems (pp. 146–150).

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1. A multilevel authentication-based blockchain powered medicine anti-counterfeiting for reliable IoT supply chain management;The Journal of Supercomputing;2023-09-21

2. Forgery Detection for Anti-Counterfeiting Patterns Using Deep Single Classifier;Applied Sciences;2023-07-11

3. Anti-counterfeiting textured pattern;The Visual Computer;2023-07-01

4. Fast Point Cloud Registration Method with Incorporation of RGB Image Information;Applied Sciences;2023-04-20

5. Robot Target Location Based on the Difference in Monocular Vision Projection;IEEE Access;2023

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