Segmentation Using CNN for BAA using Modified TW3 method

Deshmukh, Sonal; Khaparde, Arti

doi:10.1109/icecet52533.2021.9698478

2021 International Conference on Electrical, Computer and Energy Technologies (ICECET) 2021

DOI: 10.1109/icecet52533.2021.9698478

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Segmentation Using CNN for BAA using Modified TW3 method

Sonal Deshmukh¹,

Arti Khaparde²

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2023

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The Effects of the Traditional Data Augmentation Techniques on Long Bone Fracture Detection

CANGÖZ

Güney²

2023

Bilge International Journal of Science and Technology Research

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Image collection and preparation phases are highly costly for machine learning algorithms. They require the majority of labeled data. Hence, the image pre-processing method, data augmentation, is commonly used. Since there are so many proposed methods for the augmentation task, this comparison study is presented to be a supporting guide for the researchers. In addition, the lack of studies with animal-based data sets makes this study more valuable. The study is investigated on a comprehensive medical image data set consists of X-ray images of many different dogs. The main goal is to determine the fracture of the long bones in dogs. Many traditional augmentation methods are employed on the data set including flipping, rotating, changing brightness and contrast of the images. Transfer learning is applied on both raw and augmented data sets as a feature extractor and Support Vector Machine (SVM) is utilized as a classifier. For the classification task, the experimental study shows that changing the contrast is the outstanding method for accuracy manner, while the rotation method has the best sensitivity value.

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The Effects of the Traditional Data Augmentation Techniques on Long Bone Fracture Detection

CANGÖZ

Güney²

2023

Bilge International Journal of Science and Technology Research

View full text Add to dashboard Cite

show abstract

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Segmentation Using CNN for BAA using Modified TW3 method

Cited by 1 publication

References 27 publications

The Effects of the Traditional Data Augmentation Techniques on Long Bone Fracture Detection

The Effects of the Traditional Data Augmentation Techniques on Long Bone Fracture Detection

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