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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/52377
Title: The adaptive boosting algorithm in biomedical image segmentation
Authors: Zhao Di
Tang Yi
Keywords: материалы конференций;machine learning;magnetic resonance imaging;biomedical image
Issue Date: 2023
Publisher: БГУИР
Citation: Zhao Di. The adaptive boosting algorithm in biomedical image segmentation / Zhao Di, Tang Yi // Информационные технологии и управление : материалы 59-ой научной конференции аспирантов, магистрантов и студентов, Минск, 17–21 апреля 2023 года / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: Л. Ю. Шилин [и др.]. – Минск, 2023. – С. 56.
Abstract: Adaptive Boosting is a powerful machine learning algorithm that has been widely used in biomedical image segmentation due to its ability to handle high-dimensional feature spaces and improve classication accuracy. In this paper, we will introduce the principles and applications of AdaBoost and discuss its advantages and disadvantages.
URI: https://libeldoc.bsuir.by/handle/123456789/52377
Appears in Collections:Информационные технологии и управление : материалы 59-й научной конференции аспирантов, магистрантов и студентов (2023)

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