BibSLEIGH — Pasi

Travelled to:

1 × Cyprus
1 × Japan
1 × Spain
1 × Switzerland
1 × Turkey
1 × USA
2 × Canada
4 × United Kingdom

Collaborated with:

M.Xu O.Virmajoki A.Kolesnikov I.Kärkkäinen M.Chen V.Hautamäki A.Akimov P.Nykänen X.Wu T.Kaukoranta A.Mednonogov H.Kälviäinen Q.Zhao M.Rezaei H.Chen J.Kuittinen A.Tabarcea L.Sakala R.Saeidi P.Mowlaee T.Kinnunen Z.Tan M.G.Christensen S.H.Jensen

Talks about:

cluster (7) approxim (4) optim (4) compress (3) vector (3) signal (3) use (3) algorithm (2) prototyp (2) polygon (2)

Person: Pasi Fränti

DBLP: Fr=auml=nti:Pasi

Contributed to:

2012

2010

2008

2004

2002

2000

Wrote 16 papers:

ICPR-2012-ChenXF #approximate #using: Compression of GPS trajectories using optimized approximation (MC, MX, PF), pp. 3180–3183.
ICPR-2012-ZhaoRCF #automation #categorisation #clustering #keyword: Keyword clustering for automatic categorization (QZ, MR, HC, PF), pp. 2845–2848.
ICPR-2010-ChenXF: Optimized Entropy-constrained Vector Quantization of lossy Vector Map Compression (MC, MX, PF), pp. 722–725.
ICPR-2010-SaeidiMKTCJF #identification #independence #speech: Signal-to-Signal Ratio Independent Speaker Identification for Co-channel Speech Signals (RS, PM, TK, ZHT, MGC, SHJ, PF), pp. 4565–4568.
SAC-2010-FrantiKTS #architecture #concept #prototype: MOPSI location-based search engine: concept, architecture and prototype (PF, JK, AT, LS), pp. 872–873.
ICPR-2008-HautamakiNF #approximate #clustering #prototype: Time-series clustering by approximate prototypes (VH, PN, PF), pp. 1–4.
ICPR-v1-2004-VirmajokiF #algorithm #clustering #divide and conquer #graph: Divide-and-Conquer Algorithm for Creating Neighborhood Graph for Clustering (OV, PF), pp. 264–267.
ICPR-v2-2004-KolesnikovFW #approximate #multi: Multiresolution Polygonal Approximation of Digital Curves (AK, PF, XW), pp. 855–858.
ICPR-v3-2004-HautamakiKF #detection #graph #nearest neighbour #using: Outlier Detection Using k-Nearest Neighbour Graph (VH, IK, PF), pp. 430–433.
ICPR-v4-2004-XuF #clustering #difference: Delta-MSE Dissimilarity in Suboptimal K-Means Clustering (MX, PF), pp. 577–580.
SAC-2004-AlexanderF #image #representation: Symbol representation in map image compression (AA, PF), pp. 29–34.
ICPR-v2-2002-FrantiVK #bound #clustering: Branch-and-Bound Technique for Solving Optimal Clustering (PF, OV, TK), pp. 232–235.
ICPR-v2-2002-FrantiX #classification #using: Classification of Binary Vectors by Using ??SC-Distance (PF, MX), pp. 52–55.
ICPR-v2-2002-KarkkainenF #clustering: Dynamic Local Search for Clustering with Unknown Number of Clusters (IK, PF), pp. 240–243.
ICPR-v4-2002-KolesnikovF #algorithm #approximate #performance: A Fast Near-Optimal Algorithm for Approximation of Polygonal Curves (AK, PF), pp. 335–338.
ICPR-v4-2000-FrantiMK #image #invariant: Hough Transform for Rotation Invariant Matching of Line-Drawing Images (PF, AM, HK), pp. 4389–4392.