Face Image Scanning for Differentiation of Child/Adult images using a CNN-Based Model

被引：0

作者：

Ahmed, Mirza Jamal ^{[1
]}

Abdullah, Nurul Aza ^{[2
]}

机构：

[1] Univ Tun Hussain Malaysia, FSKT, Johar, Malaysia

[2] Univ Tun Hussain nN Malaysia, Johar, Malaysia

来源：

2021 IEEE ASIA-PACIFIC CONFERENCE ON COMPUTER SCIENCE AND DATA ENGINEERING (CSDE) | 2021年

关键词：

CNN; Machine Learning; Image Classification; Digital Image Forensics; CSA; Computer Vision;

D O I：

10.1109/CSDE53843.2021.9718484

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Differentiating child and adult images is a crucial requirement for many applications. This paper proposes an approach using a Convolutional Neural Network (CNN) model to distinguish between children's images from adults. In contrast to predetermined face landmarks, the suggested approach learns complex face features and achieves 85% accuracy regardless of variation in age, gender, race, or ethnicity. The approach could be used to leverage the performance of digital image forensic, security control and, surveillance monitoring, and robotics.

引用

页数：6

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