J
Jean-Yves Ramel
Researcher at François Rabelais University
Publications - 131
Citations - 1767
Jean-Yves Ramel is an academic researcher from François Rabelais University. The author has contributed to research in topics: Graph (abstract data type) & Segmentation. The author has an hindex of 20, co-authored 131 publications receiving 1542 citations. Previous affiliations of Jean-Yves Ramel include Institut national des sciences Appliquées de Lyon.
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Journal ArticleDOI
Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge
Xiahai Zhuang,Lei Li,Christian Payer,Darko Štern,Martin Urschler,Mattias P. Heinrich,Julien Oster,Chunliang Wang,Örjan Smedby,Cheng Bian,Xin Yang,Pheng-Ann Heng,Aliasghar Mortazi,Ulas Bagci,Guanyu Yang,Chenchen Sun,Gaetan Galisot,Jean-Yves Ramel,Thierry Brouard,Qianqian Tong,Weixin Si,Xiangyun Liao,Guodong Zeng,Zenglin Shi,Guoyan Zheng,Chengjia Wang,Tom MacGillivray,David E. Newby,Kawal Rhode,Sebastien Ourselin,Raad Mohiaddin,Jennifer Keegan,David N. Firmin,Guang Yang +33 more
TL;DR: This work presents the methodologies and evaluation results for the WHS algorithms selected from the submissions to the Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, in conjunction with MICCAI 2017.
Proceedings ArticleDOI
An Exact Graph Edit Distance Algorithm for Solving Pattern Recognition Problems
TL;DR: This work proposes a depth-first graph edit distance algorithm which requires less memory and searching time, and empirically demonstrated that this approach is better than the A* graph edits distance computation in terms of speed, accuracy and classification rate.
Book ChapterDOI
User classification for keystroke dynamics authentication
TL;DR: A method to realize a classification of keystroke dynamics users before performing user authentication to set automatically the individual parameters of the classification method for each class of users.
Proceedings ArticleDOI
Detection, extraction and representation of tables
TL;DR: A flexible representation scheme for complex tables is put forward, based on a clear distinction between the physical layout of a table and its logical structure, and a new method for the detection and the extraction of tables by an analysis of the graphic lines is developed.
Journal ArticleDOI
Document image characterization using a multiresolution analysis of the texture: application to old documents
TL;DR: By extracting five features linked to the frequencies and to the orientations in the different areas of a page, it is possible to extract and compare elements of high semantic level without expressing any hypothesis about the physical or logical structure of the analyzed documents.