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High-precision brain tumor segmentation with switchable normalization in faster R-CNN architecture.

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Bibliographic Details
Title:	High-precision brain tumor segmentation with switchable normalization in faster R-CNN architecture.
Authors:	Kumar DR; Department of Computer Science and Engineering, School of Engineering, Anurag University, Hyderabad, Telangana, India., Reddy PV; Department of CSE AI&ML, Keshav Memorial Engineering College, Hyderabad, Telangana, India., Mohammad H; Department of CSE (Data Science), Prasad V. Potluri Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, India., Madhu G; Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Bowrampet, Hyderabad, Telangana, 500043, India., K SB; Department of CSE (Data Science), CMR Technical Campus, Hyderabad, Telangana, India., Narender M; Department of Computer Science and Engineering, TKR College of Engineering and Technology, Hyderabad, Telangana, India. machha.narender@gmail.com., Mahendar A; Department of CSE (Data Science), CMR Technical Campus, Hyderabad, Telangana, India.
Source:	Scientific reports [Sci Rep] 2026 May 14; Vol. 16 (1). Date of Electronic Publication: 2026 May 14.
Publication Type:	Journal Article
Journal Info:	Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Database:	MEDLINE Ultimate

Description
ISSN:	2045-2322
DOI:	10.1038/s41598-026-50240-8