A Survey: Effect of the Number of GLCM Features on Classification Accuracy of Lasem Batik Images using K-Nearest Neighbor-Reference-Cited by-同舟云学术

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A Survey: Effect of the Number of GLCM Features on Classification Accuracy of Lasem Batik Images using K-Nearest Neighbor

Published:2018-11 Issue: Volume: Page:
ISSN:
Container-title:2018 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)
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Author:

Irawan Candra,Ardyastiti Ericha Nurvia,Setiadi De Rosal Ignatius Moses,Rachmawanto Eko Hari,Sari Christy Atika

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8855799/8864230/08864443.pdf?arnumber=8864443

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. Batik classification using KNN algorithm and GLCM features extraction;E3S Web of Conferences;2024

2. Pre-Processing Of Resize And Region Of Interest (ROI) To Improve The Accuracy Of Batik Detection Based On VGG-16;2023 10th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI);2023-09-20

3. Betta Fish Image Identification using Feature Extraction GLCM and K-Nearest Neighbour Classification;2022 International Conference on Information Technology Research and Innovation (ICITRI);2022-11-10

4. Quantization selection based on characteristic of cover image for PVD Steganography to optimize imperceptibility and capacity;Multimedia Tools and Applications;2022-07-11

5. Computational Adoption in Cultural Heritage: A Systematic Literature Review;2020 International Conference on Information Management and Technology (ICIMTech);2020-08

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