Paolo Piro

发表

Image retrieval via Kullback-Leibler divergence of patches of multiscale coefficients in the KNN framework

Michel Barlaud, Eric Debreuve, Paolo Piro, 2008, 2008 International Workshop on Content-Based Multimedia Indexing.

Universal k-NN (UNN) Classification of Cell Images using Histograms of DoG Coefficients

Michel Barlaud, Paolo Piro, Thierry Pourcher, 2016, BIOINFORMATICS.

Inner product tree for improved Orthogonal Matching Pursuit

Vittorio Murino, Diego Sona, Paolo Piro, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

Classification of biological cells using bio-inspired descriptors

Richard Nock, Michel Barlaud, Paolo Piro, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

Using Neighborhood Distributions of Wavelet Coefficients for On-the-Fly, Multiscale-Based Image Retrieval

Michel Barlaud, Eric Debreuve, Paolo Piro, 2008, 2008 Ninth International Workshop on Image Analysis for Multimedia Interactive Services.

From descriptor to boosting: Optimizing the k-NN classification rule

Michel Barlaud, Eric Debreuve, Paolo Piro, 2010, 2010 International Workshop on Content Based Multimedia Indexing (CBMI).

K-NN boosting prototype learning for object classification

Frank Nielsen, Richard Nock, Michel Barlaud, 2010, 11th International Workshop on Image Analysis for Multimedia Interactive Services WIAMIS 10.

Multiview Machine Learning Using an Atlas of Cardiac Cycle Motion

Paul Aljabar, Mathieu De Craene, Hélène Langet, 2017, STACOM@MICCAI.

Scalable Spatio-Temporal Video Indexing Using Sparse Multiscale Patches

Michel Barlaud, Eric Debreuve, Paolo Piro, 2009, 2009 Seventh International Workshop on Content-Based Multimedia Indexing.

Boosting k-NN for Categorization of Natural Scenes

Frank Nielsen, Richard Nock, Michel Barlaud, 2010, International Journal of Computer Vision.

A Bio-inspired Learning and Classification Method for Subcellular Localization of a Plasma Membrane Protein

Michel Barlaud, Paolo Piro, Thierry Pourcher, 2012, VISAPP.

Leveraging Κ-nn for generic classification boosting

Frank Nielsen, Michel Barlaud, Paolo Piro, 2010 .

Learning prototype-based classification rules in a boosting framework: application to real-world and medical image categorization

Paolo Piro, Paolo Piro, 2010 .

Biological cells classification using bio-inspired descriptor in a boosting k-NN framework

Michel Barlaud, Paolo Piro, Thierry Pourcher, 2012, 2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS).

Handcrafted features vs ConvNets in 2D echocardiographic images

Hélène Langet, Pascal Allain, Eric Saloux, 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017).

Boosting k-Nearest Neighbors Classification

Richard Nock, Paolo Piro, Wafa Bel Haj Ali, 2013, Advanced Topics in Computer Vision.

Multi-class Leveraged κ-NN for Image Classification

Frank Nielsen, Richard Nock, Michel Barlaud, 2010, ACCV.

Sparse Multiscale Patches for Image Processing

Michel Barlaud, Eric Debreuve, Paolo Piro, 2008, ETVC.

Sparse Multiscale Patches (SMP) for Image Categorization

Michel Barlaud, Eric Debreuve, Paolo Piro, 2009, MMM.

Leveraging Κ-nn for generic classification boosting

Frank Nielsen, Richard Nock, Michel Barlaud, 2010, 2010 IEEE International Workshop on Machine Learning for Signal Processing.

Describing the Conformational Landscape of Small Organic Molecules through Gaussian Mixtures in Dihedral Space.

Vittorio Murino, Diego Sona, Paolo Piro, 2014, Journal of chemical theory and computation.

Combining spatial and temporal patches for scalable video indexing

Michel Barlaud, Eric Debreuve, Paolo Piro, 2010, Multimedia Tools and Applications.

Learning associations between clinical information and motion-based descriptors using a large scale MR-derived cardiac motion atlas

Mathieu De Craene, Hélène Langet, Julia A. Schnabel, 2018, STACOM@MICCAI.

Boosting Bayesian MAP Classification

Frank Nielsen, Richard Nock, Michel Barlaud, 2010, 2010 20th International Conference on Pattern Recognition.

Bregman vantage point trees for efficient nearest Neighbor Queries

Frank Nielsen, Michel Barlaud, Paolo Piro, 2009, 2009 IEEE International Conference on Multimedia and Expo.

Left Ventricular Shape and Motion Reconstruction Through a Healthy Model for Characterizing Remodeling After Infarction

Nicolas Duchateau, Mathieu De Craene, Pascal Allain, 2019, FIMH.

Tailored Bregman Ball Trees for Effective Nearest Neighbors

Frank Nielsen, Michel Barlaud, Paolo Piro, 2009 .