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Bounded–abstaining classification for breast tumors in imbalanced ultrasound images Cover

Bounded–abstaining classification for breast tumors in imbalanced ultrasound images

International Journal of Applied Mathematics and Computer Science
Volume 30 (2020): Issue 2 (June 2020)
By: Hongjiao Guan,  Yingtao Zhang,  Heng-Da Cheng and  Xianglong Tang  
Open Access
|Jul 2020

Authors

Hongjiao Guan

School of Cyber Security, Qilu University of Technology, Shandong Academy of Sciences, Jinan, China
Shandong Key Laboratory of Computer Networks, Jinan, China
School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

Yingtao Zhang

yingtao@hit.edu.cn

School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

Heng-Da Cheng

School of Computer Science, Utah State University, Logan

Xianglong Tang

School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
DOI: https://doi.org/10.34768/amcs-2020-0025 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
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Language: English
Page range: 325 - 336
Submitted on: Mar 30, 2019
|
Accepted on: Dec 20, 2019
|
Published on: Jul 4, 2020
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
breast ultrasound (BUS) images,
reliable diagnosis,
abstaining classification,
imbalanced datasets
Related subjects:
Mathematics,
Applied mathematics

© 2020 Hongjiao Guan, Yingtao Zhang, Heng-Da Cheng, Xianglong Tang, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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