Comparison of spine curvature images classification using support vector machine and K-nearest neighbors-Reference-Cited by-同舟云学术

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Comparison of spine curvature images classification using support vector machine and K-nearest neighbors

Published:2022 Issue: Volume: Page:
ISSN:0094-243X
Container-title:THE 2ND INTERNATIONAL CONFERENCE OF SCIENCE AND INFORMATION TECHNOLOGY IN SMART ADMINISTRATION (ICSINTESA 2021)
language:
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Author:

Jusman Yessi,Lubis Julnila Husna,Kanafiah Siti Nurul Aqmariah Mohd,Yusof Mohd Imran

Publisher

AIP Publishing

Link

http://aip.scitation.org/doi/pdf/10.1063/5.0105008

Reference22 articles.

1. Automatic Detection of Scoliotic Curves in Posteroanterior Radiographs

2. Rule-based fuzzy classifier for spinal deformities

3. Kowalski, I.M., et al., Early detection of idiopathic scoliosis–analysis of three screening models. Archives of medical science: AMS, 2015. 11(5): p. 1058.

4. Jusman, Y., et al. Feature Extraction Performance to Differentiate Spinal Curvature Types using Gray Level Co-occurrence Matrix Algorithm. in 2020 3rd International Conference on Information and Communications Technology (ICOIACT). 2020.

5. An effective image retrieval scheme using color, texture and shape features

Cited by 2 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. Differentiating Types of Spinal Curvatures Using AlexNet and ResNet-50 Models;2023 International Conference on Information Technology and Computing (ICITCOM);2023-12-01

2. Comparison of GoogLeNet and AlexNet Models Performances for Spine Curvature Images Classification;2023 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET);2023-11-15

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