Face Recognition Accuracy Improving Using Gray Level Co-occurrence Matrix Selection Feature Algorithm

Author:

Vera 1,Kusnadi Adhi1,Pane Ivransa Zuhdi1,Overbeek Marlinda Vasty1,Prasetya Syarief Gerald1

Affiliation:

1. Universitas Multimedia Nusantara,Informatics Department,Tangerang,Indonesia

Publisher

IEEE

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Evaluation of machine learning models for mapping soil salinity in Ben Tre province, Vietnam;Multimedia Tools and Applications;2024-03-16

2. A Novel Approach for Object Recognition Using Decision Tree Clustering by Incorporating Multi-Level BPNN Classifiers and Hybrid Texture Features;International Journal of Information Retrieval Research;2024-02-19

3. A Composite Approach to Face Recognition: Integrating DCT, GLCM, and CNN;2023 IEEE 21st Student Conference on Research and Development (SCOReD);2023-12-13

4. Classification of Ettawa Crossbread Goats based on Face using Gray Level Co-Occurrence Matrix (GLCM) and Support Vector Machines (SVM) Methods;2023 International Workshop on Artificial Intelligence and Image Processing (IWAIIP);2023-12-01

5. Advancing ASD Diagnostic Classification with Features of Continuous Wavelet Transform of fMRIand Machine Learning Algorithms;2023 IEEE 5th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA);2023-10-07

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