Travelled to:1 × Brazil
1 × Germany
1 × India
1 × Korea
1 × Spain
2 × China
3 × USA
Collaborated with:P.Héroux É.Trupin E.Barbu G.El-Boussaidi Y.Lecourtier L.Heutte H.Locteau C.Chatelain T.Paquet A.Abran S.Bernard R.Raveaux T.Kasar P.Barlas P.L.Bodic A.Knippel J.Ogier C.Cariou R.Mullot J.Gardes
Talks about:use (7) multi (5) document (4) graph (4) imag (4) recognit (3) symbol (3) algorithm (2) artifact (2) approach (2)
Person: Sébastien Adam
DBLP: Adam:S=eacute=bastien
Contributed to:
2015
2013201320092007
200620062005
20051999Wrote 12 papers:
- SEKE-2015-AdamEA #approach #design
- An approach for classifying design artifacts (SA, GEB, AA), pp. 164–167.
- 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.
- SEKE-2013-AdamE #approach #multi
- A multi-dimensional approach for analyzing software artifacts (SA, GEB), pp. 650–655.
- 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-2007-BernardAH #random #recognition #using
- Using Random Forests for Handwritten Digit Recognition (SB, SA, LH), pp. 1043–1047.
- ICDAR-2007-ChatelainALHP #multi #optimisation
- Multi-Objective Optimization for SVM Model Selection (CC, SA, YL, LH, TP), pp. 427–431.
- 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.
- ICDAR-1999-AdamOCMGL #multi #recognition
- Multi-scaled and Multi-oriented Character Recognition: An Original Strategy (SA, JMO, CC, RM, JG, YL), pp. 45–48.