Late fusion of deep learning and handcrafted visual features for biomedical image modality classification-Reference-Cited by-同舟云学术

Late fusion of deep learning and handcrafted visual features for biomedical image modality classification

Published:2019-02 Issue:2 Volume:13 Page:382-391
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Lee Sheng Long¹^ORCID,Zare Mohammad Reza²,Muller Henning³

Affiliation:

1. School of Information Technology, Monash University Malaysia47500Subang JayaSelangorMalaysia

2. Department of InformaticsUniversity of LeicesterLeicesterUK

3. Information Systems Institute, University of Applied Sciences Western Switzerland (HES‐SO) ValaisSierreSwitzerland

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2018.5054

Reference56 articles.

1. 2011 2011 9th Int. Workshop on Content‐Based Multimedia Indexing (CBMI) Madrid Spain P. Tirilly K. Lu X. Mu On modality classification and its use in text‐based image retrieval in medical databases

2. A Survey on Visual Information Search Behavior and Requirements of Radiologists

3. 2013 CLEF 2013 (Cross Language Evaluation Forum) Valencia Spain A. Garcia Seco de Herrera J. Kalpathy‐Cramer D. Demner Fushman Overview of the ImageCLEF 2013 medical task

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