Book ChapterDOI
Zernike Moments and Machine Learning Based Gender Classification Using Facial Images
Vijayalakshmi G. V. Mahesh,Alex Noel Joseph Raj +1 more
- pp 398-408
TLDR
The simulation results indicate the effectiveness of the proposed zernike moments based gender classification system in achieving the greater accuracy even under the variations in pose, scale, rotation and occlusion.Abstract:
This paper proposes a zernike moments based gender classification system using facial image. Gender classification is achieved by training the Bayesian, Support vector machine, Linear discriminant analysis and Neural network classifiers. The proposed method was evaluated using ORL and faces94 databases. The simulation results indicate the effectiveness of the method in achieving the greater accuracy even under the variations in pose, scale, rotation and occlusion. In particular the neural network classifier was excellent in providing classification accuracy of 95% and 100% respectively with 25 zernike moments for ORL and faces94 database.read more
Citations
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Journal ArticleDOI
Faces Recognition and Facial Gender Classification using Convolutional Neural Network
TL;DR: The obtained results prove that the proposed CNN models are an effective solution for face image recognition and facial gender image classification, and produces competitive accuracy compared to several state-of-the-art methods.
Posted Content
Machine learning aided noise filtration and signal classification for CREDO experiment
Łukasz Bibrzycki,David Alvarez-Castillo,Olaf Bar,Dariusz Gora,Piotr Homola,Peter Kovacs,Michał Niedźwiecki,Marcin Piekarczyk,Krzysztof Rzecki,Jaroslaw Stasielak,Sławomir Stuglik,Oleksandr Sushchov,Arman Tursunov +12 more
TL;DR: In this paper, a convolutional neural network-based method of feature descriptors was proposed for detecting artefacts in the cosmic ray Extremely Distributed Observatory (CREDO) dataset.
References
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Book
Fundamentals of neural networks: architectures, algorithms, and applications
TL;DR: In this chapter seven Neural Nets based on Competition, Adaptive Resonance Theory, and Backpropagation Neural Net are studied.
Journal ArticleDOI
What's In A Name? Malay Seals As Onomastic Sources
TL;DR: This article serves both as a tutorial introduction to ROC graphs and as a practical guide for using them in research.
Journal ArticleDOI
Invariant image recognition by Zernike moments
Alireza Khotanzad,Y.H. Hong +1 more
TL;DR: A systematic reconstruction-based method for deciding the highest-order ZERNike moments required in a classification problem is developed and the superiority of Zernike moment features over regular moments and moment invariants was experimentally verified.
Book
Discovering Knowledge in Data: An Introduction to Data Mining
TL;DR: The second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis.