Travelled to:1 × Australia
1 × Brazil
1 × Germany
1 × Korea
1 × Spain
1 × Sweden
2 × China
3 × USA
Collaborated with:É.Trupin S.Adam E.Barbu M.Mehri P.Gomez-Krämer R.Mullot H.Locteau Y.Lecourtier N.Sidere J.Ramel R.Raveaux S.Diana A.Ribert A.Boucher N.Sliti N.E.B.Amara M.Mhiri M.A.Mahjoub P.L.Bodic A.Knippel
Talks about:use (7) document (6) graph (5) imag (5) symbol (4) segment (3) classif (3) represent (2) algorithm (2) cluster (2)
Person: Pierre Héroux
DBLP: H=eacute=roux:Pierre
Contributed to:
2015
20142013
201320092007200620062005
20051998Wrote 12 papers:
- DRR-2015-MehriSHGAM #documentation #image #segmentation #using
- Use of SLIC superpixels for ancient document image enhancement and segmentation (MM, NS, PH, PGK, NEBA, RM), p. 940205.
- ICPR-2014-MehriMHGMM #benchmark #documentation #evaluation #metric #performance #set
- Performance Evaluation and Benchmarking of Six Texture-Based Feature Sets for Segmenting Historical Documents (MM, MM, PH, PGK, MAM, RM), pp. 2885–2890.
- DRR-2013-MehriGHM #analysis #documentation #image #multi #segmentation #using
- Old document image segmentation using the autocorrelation function and multiresolution analysis (MM, PGK, PH, RM).
- ICDAR-2013-MehriHGBM #approach
- A Pixel Labeling Approach for Historical Digitized Books (MM, PH, PGK, AB, RM), pp. 817–821.
- ICDAR-2009-BodicLAHLK #detection #graph #integer #linear #programming #using
- Symbol Detection Using Region Adjacency Graphs and Integer Linear Programming (PLB, HL, SA, PH, YL, AK), pp. 1320–1324.
- ICDAR-2009-SidereHR #classification #graph #representation
- Vector Representation of Graphs: Application to the Classification of Symbols and Letters (NS, PH, JYR), pp. 681–685.
- ICDAR-2007-HerouxBAT #analysis #automation #comprehension #documentation #generative #image
- Automatic Ground-truth Generation for Document Image Analysis and Understanding (PH, EB, SA, ÉT), pp. 476–480.
- ICPR-v2-2006-LocteauRALHT #algorithm #approximate #multi #search-based #using
- Approximation of Digital Curves using a Multi-Objective Genetic Algorithm (HL, RR, SA, YL, PH, ÉT), pp. 716–719.
- ICPR-v3-2006-BarbuRLAHT #algorithm #classification #graph #recognition #search-based #using
- Graph Classification Using Genetic Algorithm and Graph Probing Application to Symbol Recognition (EB, RR, HL, SA, PH, ÉT), pp. 296–299.
- ICDAR-2005-BarbuHAT #clustering #documentation #image #representation #using
- Clustering document images using a bag of symbols representation (EB, PH, SA, ÉT), pp. 1216–1220.
- MLDM-2005-BarbuHAT #clustering #documentation #graph #image #summary #using
- Clustering Document Images Using Graph Summaries (EB, PH, SA, ÉT), pp. 194–202.
- ICPR-1998-HerouxDRT #automation #classification #identification
- Classification method study for automatic form class identification (PH, SD, AR, ÉT), pp. 926–928.