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Digne J, Dimiccoli M, Salembier P, Sabater N. Neighborhood Filters and the Recovery of 3D Information. In Handbook of Mathematical Methods in Imaging. Springer Verlag; 2011. pp. 1203-1229.
Digne J, Dimiccoli M, Sabater N, Salembier P. Neighborhood Filters and the Recovery of 3D Information. In Handbook of Mathematical Methods in Imaging. 2nd ed. Springer Verlag; 2015. pp. 1645-1673.
Bellot P, Olsen C, Salembier P, Oliveras A, Meyer PE. NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference. BMC Bioinformatics. 2015;16.  (851.49 KB)
Dominguez A, Mas-Montserrat D, Bustamante C, Giró-i-Nieto X, Ioannidis AG. Neural ADMIXTURE: rapid population clustering with autoencoders. In 2021 Society for Molecular Biology & Evolution meeting (SMBEv2021). Virtual; 2021.  (1.76 MB)
Dominguez A, Mas-Montserrat D, Bustamante C, Giró-i-Nieto X, Ioannidis AG. Neural ADMIXTURE: rapid population clustering with autoencoders. Nature Computational Science. In Press;.
Pardàs M, Sayrol E. A new approach to active contours for tracking. In IEEE International Conference on Image Processing. 2000.
Gimeno D, Torres L, Casas J. A new approach to texture coding using stochastic vector quantization. In IEEE International Conference on Image Processing'94. 1994. pp. 119–123.
Torres L, Casas J. New approaches to texture coding in segmentation and feature-based image coding schemes. In International Conference on Digital Signal Processing. 1995. pp. 12–17.
Marqués F. NEW GENERATION METHODS FOR HTE HIGH-COMPRESSION CODING OF DIGITAL SEQUENCES. In From pixels to features ii. 1990. pp. 363–375.
Valero S, Salembier P, Chanussot J. New hyperspectral data representation using binary partition tree. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010. Honolulu, USA; 2010. pp. 80–83.  (120 KB)
Barkhuus L, Zoric G, Engström A, Ruiz-Hidalgo J, Verzijp N. New interaction modes for rich panoramic live video experiences. Behaviour & Information Technology. 2014;33(8).
Nguyen V-T, -Dinh-Le D, Salvador A, -Zhu C, Nguyen D-L, Tran M-T, et al.. NII-HITACHI-UIT at TRECVID 2015 Instance Search. In TRECVID 2015 Workshop. Gaithersburg, MD, USA: NIST; 2015.  (1.53 MB)
Puch S. Nonlinear analysis toolbox for neurodegenerative diseases and aging. Vilaplana V. 2016.  (9.74 MB)
Gasull A, Marqués F, Torres L. Non-linear techniques for image interpolation. In VI European Signal Processing Conference. 1992. pp. 1473–1476.
Vidal J, Sayrol E, Cabanillas S, Santamaría S. Non-Noticeable Information Embedding in Color Images : Marking and Detection. In 33rd ANNUAL - 1999 International Carnahan Conference on Security Technology. 1999. pp. 293–297.
Haro G, Lenglet C, Sapiro G, Thompson P. On the non-uniform complexity of brain connectivity. In 5th IEEE International Symposium on Biomedical Imaging (ISBI 2008). Paris: IEEE; 2008.  (2.2 MB)
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Vilaplana V, Marqués F, León M, Gasull A. Object detection and segmentation on a hierarchical region-based image representation. In 2010 IEEE International Conference on Image Processing. 2010. pp. 3393–3396.
Giró-i-Nieto X, Ventura C. Object Detection with Deep Learning. 2021.
Marqués F, Pardàs M, Morros JR. Object matching based on partition information. In IEEE International Conference on Image Processing. 2002. pp. 829–832.  (317.46 KB)
Escobar M. Object Model Adaptation for Multiple Object Tracking. Girbau A, Ventura C, Giró-i-Nieto X, Marqués F. 2021 .  (785.3 KB)
Salerno O, Pardàs M, Vilaplana V, Marqués F. Object recognition based on Binary Partition Trees. In IEEE International Conference on Image Processing. 2004. pp. 929–932.
Valero S, Salembier P, Chanussot J. Object recognition in hyperspectral images using Binary Partition Tree representation. Pattern Recognition Letters. 2015;56:45-51.  (1.75 MB)
Valero S, Salembier P, Chanussot J. Object recognition in urban hyperspectral images using binary partition tree representation. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS'2013. Melbourne, Australia: IEEE; 2013.  (498.43 KB)
Ferran C, Casas J. Object representation using colour, shape and structure criteria in a Binary Partition Tree. In IEEE International Conference on Image Processing. 2005.
Mohedano E, Salvador A, McGuinness K, Giró-i-Nieto X, O'Connor N, Marqués F. Object Retrieval with Deep Convolutional Features. In Deep Learning for Image Processing Applications. Amsterdam, The Netherlands: IOS Press; 2017.

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