Travelled to:1 × Australia
1 × Austria
1 × Brazil
1 × Canada
1 × China
1 × Germany
1 × Japan
1 × Turkey
2 × USA
Collaborated with:D.Prusa V.Franc P.Krízek J.Kittler T.Werner T.Pajdla L.Cerman A.Shekhovtsov M.Bresler K.Antoniuk A.Imiya K.Tatara H.Ootani A.Leonardis
Talks about:select (3) featur (3) imag (3) base (3) recognit (2) problem (2) model (2) learn (2) set (2) represent (1)
Person: Václav Hlavác
DBLP: Hlav=aacute=c:V=aacute=clav
Contributed to:
2013
20122010200820072006
2003200219981996Wrote 11 papers:
- ICDAR-2013-BreslerPH #modelling #problem #recognition
- Modeling Flowchart Structure Recognition as a Max-Sum Problem (MB, DP, VH), pp. 1215–1219.
- ICPR-2012-AntoniukFH #learning #markov #network
- Learning Markov Networks by Analytic Center Cutting Plane Method (KA, VF, VH), pp. 2250–2253.
- ICPR-2012-CermanH #learning #problem
- Tracking with context as a semi-supervised learning and labeling problem (LC, VH), pp. 2124–2127.
- ICPR-2010-ShekhovtsovH #estimation #image
- Joint Image GMM and Shading MAP Estimation (AS, VH), pp. 1360–1363.
- ICPR-2008-KrizekKH #algorithm #feature model
- Feature condensing algorithm for feature selection (PK, JK, VH), pp. 1–4.
- ICDAR-2007-PrusaH #2d #recognition #using
- Mathematical Formulae Recognition Using 2D Grammars (DP, VH), pp. 849–853.
- ICPR-v2-2006-KrizekKH #feature model #set
- Feature selection based on the training set manipulation (PK, JK, VH), pp. 658–661.
- MLDM-2003-ImiyaTOH #bound #detection #random #set
- Detecting the Boundary Curve of Planar Random Point Set (AI, KT, HO, VH), pp. 413–424.
- ICPR-v2-2002-FrancH #multi
- Multi-Class Support Vector Machine (VF, VH), pp. 236–239.
- ICPR-1998-WernerPH #performance #visualisation
- Efficient rendering of projective model for image-based visualization (TW, TP, VH), pp. 1705–1707.
- ICPR-1996-WernerHLP #representation
- Selection of reference views for image-based representation (TW, VH, AL, TP), pp. 73–77.