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Travelled to:
1 × Austria
1 × Brazil
1 × India
1 × Korea
1 × Spain
1 × Turkey
1 × United Kingdom
2 × China
2 × France
4 × USA
Collaborated with:
L.Heutte S.Nicolas Y.Kessentini C.Chatelain U.Garain Y.Lecourtier D.Hebert N.Ragot A.B.Hamadou K.Ait-Mohand G.Bideault L.Mioulet C.Olivier S.Adam A.B.Salah T.Burger A.Guermazi A.Bensefia G.Koch S.Thomas S.K.Parui J.Dardenne A.Nosary N.Feray D.d.Brucq K.Romeo-Pakker M.Avila S.Brunessaux T.Kasar P.Barlas T.Palfray P.Tranouez J.Moreau
Talks about:
handwritten (14) document (10) recognit (9) multi (6) word (6) use (6) extract (5) segment (4) model (4) adapt (4)

Person: Thierry Paquet

DBLP DBLP: Paquet:Thierry

Contributed to:

DRR 20152015
DRR 20132013
ICDAR 20132013
DocEng 20122012
ICDAR 20112011
DRR 20102010
ICPR 20102010
ICDAR 20092009
ICDAR 20072007
ICPR v3 20062006
ICDAR 20052005
DocEng 20032003
ICDAR 20032003
ICDAR 19991999
ICPR 19961996
ICDAR v1 19951995

Wrote 30 papers:

DRR-2015-BideaultMCP #architecture #regular expression #using #word
Spotting handwritten words and REGEX using a two stage BLSTM-HMM architecture (GB, LM, CC, TP).
DRR-2015-MiouletBCPB #architecture #multi #network #recognition
Exploring multiple feature combination strategies with a recurrent neural network architecture for off-line handwriting recognition (LM, GB, CC, TP, SB).
DRR-2013-SalahRP #adaptation #assessment #automation #detection #quality
Adaptive detection of missed text areas in OCR outputs: application to the automatic assessment of OCR quality in mass digitization projects (ABS, NR, TP).
ICDAR-2013-HebertNP #documentation #framework #image
Discrete CRF Based Combination Framework for Document Image Binarization (DH, SN, TP), pp. 1165–1169.
ICDAR-2013-KasarBACP #detection #documentation #image #learning #using
Learning to Detect Tables in Scanned Document Images Using Line Information (TK, PB, SA, CC, TP), pp. 1185–1189.
ICDAR-2013-KessentiniCP #detection #documentation #regular expression #word
Word Spotting and Regular Expression Detection in Handwritten Documents (YK, CC, TP), pp. 516–520.
DocEng-2012-PalfrayHNTP #logic #segmentation
Logical segmentation for article extraction in digitized old newspapers (TP, DH, SN, PT, TP), pp. 129–132.
ICDAR-2011-BurgerKP #recognition #word
Dempster-Shafer Based Rejection Strategy for Handwritten Word Recognition (TB, YK, TP), pp. 528–532.
ICDAR-2011-HebertPN #multi
Continuous CRF with Multi-scale Quantization Feature Functions Application to Structure Extraction in Old Newspaper (DH, TP, SN), pp. 493–497.
ICDAR-2011-KessentiniPG #algorithm #multi #recognition #word
An Optimized Multi-stream Decoding Algorithm for Handwritten Word Recognition (YK, TP, AG), pp. 192–196.
DRR-2010-Ait-MohandHPR #adaptation
Font adaptation of an HMM-based OCR system (KAM, LH, TP, NR), pp. 1–10.
ICPR-2010-Ait-MohandPRH #adaptation
Structure Adaptation of HMM Applied to OCR (KAM, TP, NR, LH), pp. 2877–2880.
ICPR-2010-ThomasCHP #documentation #information management
An Information Extraction Model for Unconstrained Handwritten Documents (ST, CC, LH, TP), pp. 3412–3415.
ICDAR-2009-GarainP #identification #multi #using
Off-Line Multi-Script Writer Identification Using AR Coefficients (UG, TP), pp. 991–995.
ICDAR-2009-KessentiniPB #multi #recognition
A Multi-Lingual Recognition System for Arabic and Latin Handwriting (YK, TP, ABH), pp. 1196–1200.
ICDAR-2007-ChatelainALHP #multi #optimisation
Multi-Objective Optimization for SVM Model Selection (CC, SA, YL, LH, TP), pp. 427–431.
ICDAR-2007-GarainPPH
Machine Dating of Handwritten Manuscripts (UG, SKP, TP, LH), pp. 759–763.
ICDAR-2007-KessentiniPB #approach #multi #recognition #word
A Multi-stream Approach to Off-Line Handwritten Word Recognition (YK, TP, ABH), pp. 317–321.
ICDAR-2007-NicolasDPH #2d #documentation #image #random #segmentation #using
Document Image Segmentation Using a 2D Conditional Random Field Model (SN, JD, TP, LH), pp. 407–411.
ICPR-v3-2006-ChatelainHP #documentation
A two-stage outlier rejection strategy for numerical field extraction in handwritten documents (CC, LH, TP), pp. 224–227.
ICPR-v3-2006-NicolasPH #approach #documentation #markov #segmentation
A Markovian Approach for Handwritten Document Segmentation (SN, TP, LH), pp. 292–295.
ICDAR-2005-GarainPH #documentation #image #on the #quality
On Foreground-Background Separation in Low Quality Color Document Images (UG, TP, LH), pp. 585–589.
ICDAR-2005-NicolasKPH #documentation #markov #random #segmentation #using
Handwritten Document Segmentation Using Hidden Markov Random Fields (SN, YK, TP, LH), pp. 212–216.
DocEng-2003-NicolasPH
Digitizing cultural heritage manuscripts: the Bovary project (SN, TP, LH), pp. 55–57.
ICDAR-2003-BensefiaPH #identification #information retrieval
Information Retrieval Based Writer Identification (AB, TP, LH), pp. 946–950.
ICDAR-2003-KochHP #documentation #sequence
Numerical Sequence Extraction in Handwritten Incoming Mail Documents (GK, LH, TP), pp. 369–373.
ICDAR-1999-NosaryHPL #adaptation #invariant #recognition
Defining Writer’s Invariants to Adapt the Recognition Task (AN, LH, TP, YL), pp. 765–768.
ICPR-1996-HeutteMPLO #recognition #statistics
Combining structural and statistical features for the recognition of handwritten characters (LH, JVM, TP, YL, CO), pp. 210–214.
ICDAR-v1-1995-FerayBRP #evaluation #recognition
Evaluation of codes and primitives: recognition of unconstrained handwritten numerals (NF, DdB, KRP, TP), pp. 104–107.
ICDAR-v1-1995-OlivierPAL #modelling #probability #recognition #using #word
Recognition of handwritten words using stochastic models (CO, TP, MA, YL), pp. 19–23.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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