Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Hasan Ertan Cetingul"'
Autor:
Wilburn E. Reddick, Qiang Li, Tim Holland-Letz, Marc-Alexandre Côté, Alexander Leemans, Eleftherios Garyfallidis, Jidan Zhong, Martijn Froeling, Samuel St-Jean, Tim B. Dyrby, Maxime Chamberland, Ye Wu, Hamed Y. Mesri, Boris Mailhe, David Romascano, Yuanjing Feng, Peter F. Neher, Wes Hodges, Antonio Cerasa, Claus C. Hilgetag, Pedro Luque Laguna, Jason D. Yeatman, Szabolcs David, Julio E. Villalon-Reina, Bram Stieltjes, Oscar Esteban, Luis Miguel Lacerda, Samuel Deslauriers-Gauthier, Alessandro Daducci, Jieyan Ma, Laurent Petit, Anna Auría, Hasan Ertan Cetingul, Muhamed Barakovic, Jasmeen Sidhu, Ying-Chia Lin, Ali R. Khan, Anneriet M. Heemskerk, Klaus H. Maier-Hein, Emmanuel Caruyer, Gabriel Girard, Simona M. Brambati, Benjamin L. Odry, Qing Ji, Carl-Fredrik Westin, François Rheault, Fang-Cheng Yeh, Maxime Descoteaux, Matthieu Desrosiers, Jean-Christophe Houde, Roberta Vasta, Chengfeng Gao, Marco Catani, Julien Doyon, David Qixiang Chen, Fabrizio Pizzagalli, Mariappan S. Nadar, Arnaud Boré, Alessia Sarica, J. Omar Ocegueda Gonzalez, Fenghua Guo, H Renjie, Gautam Prasad, Basile Pinsard, Christophe Bedetti, Aldo Quattrone, Rachel Barrett, Jean-Philippe Thiran, Justin Galvis, Flavio Dell'Acqua, Francisco De Santiago Requejo, Michael Paquette, Simon Alexander, Paul M. Thompson, John O. Glass, Chantal M. W. Tax, Alia Lemkaddem
Fiber tractography based on non-invasive diffusion imaging is at the heart of connectivity studies of the human brain. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain dataset with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a937a2780535aff2c8735433d68f62c9
https://doi.org/10.1101/084137
https://doi.org/10.1101/084137
Publikováno v:
Machine Learning in Medical Imaging ISBN: 9783319471563
MLMI@MICCAI
MLMI@MICCAI
We present a learning-based framework for automatic brain extraction in MR images. It accepts single or multi-contrast brain MR data, builds global binary random forests classifiers at multiple resolution levels, hierarchically performs voxelwise cla
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::29fad2d456372f05a65284826ffae32e
https://doi.org/10.1007/978-3-319-47157-0_16
https://doi.org/10.1007/978-3-319-47157-0_16
Publikováno v:
Signal Processing. 86:3549-3558
We present a new multimodal speaker/speech recognition system that integrates audio, lip texture and lip motion modalities. Fusion of audio and face texture modalities has been investigated in the literature before. The emphasis of this work is to in
Publikováno v:
IEEE Transactions on Image Processing. 15:2879-2891
There have been several studies that jointly use audio, lip intensity, and lip geometry information for speaker identification and speech-reading applications. This paper proposes using explicit lip motion information, instead of or in addition to li
Publikováno v:
Medical Imaging: Computer-Aided Diagnosis
We have recently developed a dynamic infrared (IR) imaging system that provides accurate measurements of transient thermal response of the skin surface for characterizing lesions. Our hypothesis was that malignant pigmented lesions with increased pro
Publikováno v:
IEEE transactions on bio-medical engineering. 58(6)
The extraction of the cardiac Purkinje system (PS) from intensity images is a critical step toward the development of realistic structural models of the heart. Such models are important for uncovering the mechanisms of cardiac disease and improving i
Autor:
Hasan Ertan Cetingul, René Vidal
Publikováno v:
CVPR
The mean shift algorithm, which is a nonparametric density estimator for detecting the modes of a distribution on a Euclidean space, was recently extended to operate on analytic manifolds. The extension is extrinsic in the sense that the inherent opt
Publikováno v:
ICASSP (1)
The paper addresses the selection of robust lip-motion features for an audio-visual open-set speaker identification problem. We consider two alternatives for initial lip motion representation. In the first alternative, the feature vector is composed
Publikováno v:
ICIP
This paper addresses the selection of best lip motion features for biometric open-set speaker identification. The best features are those that result in the highest discrimination of individual speakers in a population. We first detect the face regio
Publikováno v:
Proceedings of the IEEE 12th Signal Processing and Communications Applications Conference, 2004..
The paper addresses the selection of the best lip motion features for biometric open-set speaker identification. The best features are those that result in the highest discrimination of individual speakers in a population. We first detect the face re