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Publications ~ Mikael Carlavan Wednesday, July 17th 2024, 20:11

Publications of Mikael Carlavan

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@ARTICLE{ScarpaTIP09,
	author = { Scarpa, G. and Gaetano, R. and Haindl, M. and Zerubia, J. },
	title = {  Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation },
	year = { 2009 },
	month = { August },
	journal = { IEEE Trans. on Image Processing },
	volume = { 18 },
	number = { 8 },
	pages = { 1830-1843 },
	url = { http://ieeexplore.ieee.org/xpls/abs_all.jsp?isnumber=5161445&arnumber=4914796&count=21&index=11 },
	keyword = { Hierarchical Image Models, Markov Process, Pattern Analysis }
 }

@INPROCEEDINGS{scarpa_icassp_07,
	author = { Scarpa, G. and Haindl, M. and Zerubia, J. },
	title = { A Hierarchical finite-state model for texture segmentation },
	year = { 2007 },
	month = { April },
	booktitle = { Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) },
	volume = { 1 },
	pages = { 1209-1212 },
	address = { Honolulu, HI (USA) },
	url = { http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4217303 }
 }

@INPROCEEDINGS{scarpa_scia_07,
	author = { Scarpa, G. and Haindl, M. and Zerubia, J. },
	title = { A Hierarchical Texture Model for Unsupervised Segmentation of Remotely Sensed Images },
	year = { 2007 },
	month = { June },
	booktitle = { Scandinavian Conference on Image Analysis },
	volume = { 4522/2007 },
	pages = { 303-312 },
	series = { LNCS 4522 },
	editor = { Springer Berlin / Heidelberg },
	address = { Aalborg, Denmark },
	url = { http://link.springer.com/chapter/10.1007%2F978-3-540-73040-8_31 }
 }

@TECHREPORT{scarparr06,
	author = { Scarpa, G. and Haindl, M. and Zerubia, J. },
	title = { Hierarchical finite-state modeling for texture segmentation with application to forest classification },
	year = { 2006 },
	month = { December },
	institution = { INRIA },
	type = { Research Report },
	number = { 6066 },
	address = { INRIA, France },
	url = { https://hal.inria.fr/inria-00118420 },
	keyword = { Texture, Segmentation, Co-occurrence matrix, Structural approach, MCMC, Synthesis }
 }



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