An augmented mammogram image dataset and its performance analysis for various classification models
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-14566-z.pdf
Reference45 articles.
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2. Albalawi U, Manimurugan S, Varatharajan R (2020) “Classification of breast cancer mammogram images using convolution neural network”. Concurrency and Computation: Practice and Experience, e5803
3. American Cancer Society (2021) “Cancer Facts & Figures 2021”
4. Arar M, A. Shamir, Bermano A. (2021) "In Augment: improving classifiers via internal augmentation." 2021 IEEE/CVF international conference on computer vision workshops (ICCVW). pp. 1698-1707
5. Bakalo R, Goldberger J, Ben-Ari R (2021) Weakly and semi supervised detection in medical imaging via deep dual branch net. Neurocomputing 421:15–25
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1. Similar Intensity-Based Euclidean Distance Feature Vector for Mammogram Image Classification;Advances in Data and Information Sciences;2024
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