Deformable dilated faster R-CNN for universal lesion detection in CT images

Download full text files

  • 91487.pdfeng
    (429KB)

    Postprint. © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Export metadata

Statistics

Number of document requests

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Fabio HellmannORCiDGND, Zhao RenORCiD, Elisabeth AndréORCiDGND, Björn W. SchullerORCiDGND
URN:urn:nbn:de:bvb:384-opus4-914873
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/91487
ISBN:978-1-7281-1180-3OPAC
Parent Title (English):43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC 2021), 1-5 November 2021, Mexico
Publisher:IEEE
Place of publication:New York, NY
Editor:Riccardo Barbieri
Type:Part of a Book
Language:English
Year of first Publication:2021
Publishing Institution:Universität Augsburg
Release Date:2021/12/22
First Page:2896
Last Page:2902
DOI:https://doi.org/10.1109/embc46164.2021.9631021
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Menschzentrierte Künstliche Intelligenz
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Embedded Intelligence for Health Care and Wellbeing
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht