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Author
Title
Year
Publication
Volume
Pages
Links
Katerine Diaz; Aura Hernandez-Sabate; Antonio Lopez
A reduced feature set for driver head pose estimation
2016
Applied Soft Computing
45
98-107
Aura Hernandez-Sabate; Debora Gil;Eduard Fernandez-Nofrerias;Petia Radeva; Enric Marti
Approaching Artery Rigid Dynamics in IVUS
2009
IEEE Transactions on Medical Imaging
28
1670-1680
Debora Gil; Aura Hernandez-Sabate; Antoni Carol; Oriol Rodriguez; Petia Radeva
A Deterministic-Statistic Adventitia Detection in IVUS Images
2005
ESC Congress
Debora Gil; Aura Hernandez-Sabate; Antoni Carol; Oriol Rodriguez; Petia Radeva
A Deterministic-Statistic Adventitia Detection in IVUS Images
2005
3rd International workshop on International Workshop on Functional Imaging and Modeling of the Heart
65-74
Katerine Diaz; Jesus Martinez del Rincon; Aura Hernandez-Sabate
Decremental generalized discriminative common vectors applied to images classification
2017
Knowledge-Based Systems
131
46-57
Debora Gil; Aura Hernandez-Sabate; Oriol Rodriguez; Josepa Mauri; Petia Radeva
Statistical Strategy for Anisotropic Adventitia Modelling in IVUS
2006
IEEE Transactions on Medical Imaging
25
768-778
Aura Hernandez-Sabate; Jose Elias Yauri; Pau Folch; Miquel Angel Piera; Debora Gil
Recognition of the Mental Workloads of Pilots in the Cockpit Using EEG Signals
2022
Applied Sciences
12
2298
Jose Elias Yauri; Aura Hernandez-Sabate; Pau Folch; Debora Gil
Mental Workload Detection Based on EEG Analysis
2021
Artificial Intelligent Research and Development. Proceedings 23rd International Conference of the Catalan Association for Artificial Intelligence.
339
268-277
Aura Hernandez-Sabate; Debora Gil; Petia Radeva
On the usefulness of supervised learning for vessel border detection in IntraVascular Imaging
2005
Proceeding of the 2005 conference on Artificial Intelligence Research and Development
67-74
Spyridon Bakas; Mauricio Reyes; Andras Jakab; Stefan Bauer; Markus Rempfler; Alessandro Crimi; Russell Takeshi Shinohara; Christoph Berger; Sung Min Ha; Martin Rozycki; Marcel Prastawa; Esther Alberts; Jana Lipkova; John Freymann; Justin Kirby; Michel Bilello; Hassan Fathallah-Shaykh; Roland Wiest; Jan Kirschke; Benedikt Wiestler; Rivka Colen; Aikaterini Kotrotsou; Pamela Lamontagne; Daniel Marcus; Mikhail Milchenko; Arash Nazeri; Marc-Andre Weber; Abhishek Mahajan; Ujjwal Baid; Dongjin Kwon; Manu Agarwal; Mahbubul Alam; Alberto Albiol; Antonio Albiol; Varghese Alex; Tuan Anh Tran; Tal Arbel; Aaron Avery; Subhashis Banerjee; Thomas Batchelder; Kayhan Batmanghelich; Enzo Battistella; Martin Bendszus; Eze Benson; Jose Bernal; George Biros; Mariano Cabezas; Siddhartha Chandra; Yi-Ju Chang; Joseph Chazalon; Shengcong Chen; Wei Chen; Jefferson Chen; Kun Cheng; Meinel Christoph; Roger Chylla; Albert Clérigues; Anthony Costa; Xiaomeng Cui; Zhenzhen Dai; Lutao Dai; Eric Deutsch; Changxing Ding; Chao Dong; Wojciech Dudzik; Theo Estienne; Hyung Eun Shin; Richard Everson; Jonathan Fabrizio; Longwei Fang; Xue Feng; Lucas Fidon; Naomi Fridman; Huan Fu; David Fuentes; David G Gering; Yaozong Gao; Evan Gates; Amir Gholami; Mingming Gong; Sandra Gonzalez-Villa; J Gregory Pauloski; Yuanfang Guan; Sheng Guo; Sudeep Gupta; Meenakshi H Thakur; Klaus H Maier-Hein; Woo-Sup Han; Huiguang He; Aura Hernandez-Sabate; Evelyn Herrmann; Naveen Himthani; Winston Hsu; Cheyu Hsu; Xiaojun Hu; Xiaobin Hu; Yan Hu; Yifan Hu; Rui Hua
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
2018
Arxiv
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