J
Juan Manuel Górriz
Researcher at University of Granada
Publications - 403
Citations - 8595
Juan Manuel Górriz is an academic researcher from University of Granada. The author has contributed to research in topics: Support vector machine & Computer science. The author has an hindex of 43, co-authored 360 publications receiving 6429 citations. Previous affiliations of Juan Manuel Górriz include University of Cádiz & University of Cambridge.
Papers
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Proceedings ArticleDOI
Analysis of 18F-DMFP PET data using multikernel classification in order to assist the diagnosis of Parkinsonism
Fermín Segovia,Juan Manuel Górriz,Javier Ramírez,Johannes Levin,Madeleine Schuberth,Matthias Brendel,Axel Rominger,Gaëtan Garraux,Christophe Phillips +8 more
TL;DR: This work demonstrates a full automatic computer system based on DMFP-PET data to separate idiopathic and non-idiopATHic PD patients and uses a multiple kernel learning approach to deal with the information contained in the neuroimages.
Journal ArticleDOI
Optimizing blind source separation with guided genetic algorithms
TL;DR: A novel method for blindly separating unobservable independent component (IC) signals based on the use of a genetic algorithm, able to extract IC with faster rate than the previous ICA algorithms, as input space dimension increases.
Book ChapterDOI
Hybridizing Sparse Component Analysis with Genetic Algorithms for Blind Source Separation
K. Stadlthanner,Fabian J. Theis,Carlos G. Puntonet,Juan Manuel Górriz,Ana Maria Tomé,Elmar Lang +5 more
TL;DR: First results of an extension to the NMF algorithm are presented which solves the BSS problem when the underlying sources are sufficiently sparse and the proposed target function has many local minima.
Journal ArticleDOI
Label aided deep ranking for the automatic diagnosis of Parkinsonian syndromes
TL;DR: A classification method based on Deep Ranking which learns an embedding function that projects the source images into a new space in which samples belonging to the same class are closer to each other, while samples from different classes are moved apart is proposed.
Journal ArticleDOI
Effective diagnosis of Alzheimer’s disease by means of large margin-based methodology
R. Chaves,Javier Ramírez,Juan Manuel Górriz,Ignacio A. Illán,Manuel Gómez-Río,Cristobal Carnero +5 more
TL;DR: One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable.