J. Lapuyade-Lahorgue

发表

Radar detection using Siegel distance between autoregressive processes, application to HF and X-band radar

F. Barbaresco, J. Lapuyade-Lahorgue, Frédéric Barbaresco, 2008, 2008 IEEE Radar Conference.

Unsupervised Segmentation of Hidden Semi‐Markov Non Stationary Chains

W. Pieczynski, J. Lapuyade-Lahorgue, 2006 .

A MATLAB TOOLBOX FOR DATA REDUCTION , VISUALIZATION , CLASSIFICATION AND KNOWLEDGE EXTRACTION OF COMPLEX BIOLOGICAL DATA

A. Mohammad-Djafari, J. Lapuyade-Lahorgue, G. Khodabandelou, 2011 .

SPEQTACLE: An automated generalized fuzzy C-means algorithm for tumor delineation in PET.

Jérôme Lapuyade-Lahorgue, Dimitris Visvikis, Mathieu Hatt, 2015, Medical physics.

Jérôme Lapuyade-Lahorgue Modeling of human motion and implementation of human motion tracker

J. Lapuyade-Lahorgue, 2009 .

The epimorphisms of the category Haus are exactly the image-dense morphisms.

J. Lapuyade-Lahorgue, 2018, 1810.00778.

Deep Learning Using Havrda-Charvat Entropy for Classification of Pulmonary Optical Endomicroscopy

S. Ruan, J. Lapuyade-Lahorgue, T. Brochet, 2021 .

Deep learning using Havrda-Charvat entropy for classification of pulmonary endomicroscopy pdf

Jérôme Lapuyade-Lahorgue, Su Ruan, Sébastien Bougleux, 2021, ArXiv.

Deep learning based automatic detection of uninformative images in pulmonary optical endomicroscopy

Su Ruan, Sébastien Bougleux, Thibaud Brochet, 2020, 2020 Tenth International Conference on Image Processing Theory, Tools and Applications (IPTA).

A framework based on hidden Markov trees for multimodal PET/CT image co‐segmentation

Emmanuel Monfrini, Julien Bert, Wojciech Pieczynski, 2017, Medical physics.

Deep Learning Approaches for Data Augmentation in Medical Imaging: A Review

J. Lapuyade-Lahorgue, S. Ruan, Aghiles Kebaili, 2023, J. Imaging.

Unsupervised segmentation of new semi-Markov chains hidden with long dependence noise

Wojciech Pieczynski, Jérôme Lapuyade-Lahorgue, W. Pieczynski, 2010, Signal Process..

Segmentation of multicorrelated images with copula models and conditionally random fields

J. Lapuyade-Lahorgue, S. Ruan, 2022, Journal of medical imaging.

A Quantitative Comparison between Shannon and Tsallis–Havrda–Charvat Entropies Applied to Cancer Outcome Prediction

J. Lapuyade-Lahorgue, S. Ruan, P. Vera, 2022, Entropy.

Unsupervised segmentation of randomly switching data hidden with non-Gaussian correlated noise

Pierre Lanchantin, Wojciech Pieczynski, Jérôme Lapuyade-Lahorgue, 2011, Signal Process..

Unsupervised segmentation of hidden semi-Markov non-stationary chains

Wojciech Pieczynski, Jérôme Lapuyade-Lahorgue, W. Pieczynski, 2006, Signal Process..

Semi-automatic lymphoma detection and segmentation using fully conditional random fields

Su Ruan, Pierre Vera, Isabelle Gardin, 2018, Comput. Medical Imaging Graph..

Tumor segmentation by fusion of MRI images using copula based statistical methods

J. Lapuyade-Lahorgue, S. Ruan, P. Vera, 2016, 2016 IEEE International Conference on Image Processing (ICIP).

Partially Markov models and unsupervised segmentation of semi-Markov chains hidden with long dependence noise

Jérôme Lapuyade-Lahorgue, Wojciech Pieczynski, W. Pieczynski, 2007 .

Segmenting Multi-Source Images Using Hidden Markov Fields With Copula-Based Multivariate Statistical Distributions

Su Ruan, Jing-Hao Xue, Jérôme Lapuyade-Lahorgue, 2017, IEEE Transactions on Image Processing.

SPEQTACLE: A new fuzzy clustering algorithm for fully automatic delineation of tumors in PET images

Dimitris Visvikis, Mathieu Hatt, Jerome Lapuyade-Lahorgue, 2014 .

Prediction of Head-Neck Cancer Recurrence from Pet/CT Images with Havrda-Charvat Entropy

J. Lapuyade-Lahorgue, P. Decazes, Thibaud Brochet, 2023, 2023 Twelfth International Conference on Image Processing Theory, Tools and Applications (IPTA).

Unsupervised segmentation of triplet Markov chains hidden with long-memory noise

Pierre Lanchantin, Wojciech Pieczynski, Jérôme Lapuyade-Lahorgue, 2008, Signal Process..

Tumor segmentation by fusion of MRI images using copula based statistical methods

J. Lapuyade-Lahorgue, S. Ruan, P. Vera, 2016, ICIP.

Modeling and Unsupervised Classification of Multivariate Hidden Markov Chains With Copulas

Nicolas Brunel, Wojciech Pieczynski, Jérôme Lapuyade-Lahorgue, 2010, IEEE Transactions on Automatic Control.

End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks

J. Lapuyade-Lahorgue, Aghiles Kebaili, Pierre Vera, 2023, ArXiv.