`Travelled to:`

1 × Australia

1 × Austria

1 × Canada

1 × China

1 × Germany

1 × Spain

1 × Turkey

1 × United Kingdom

`Collaborated with:`

P.Somol P.Pudil J.Hora ∅ M.Haindl M.Kudo J.Novovicová F.J.Ferri

`Talks about:`

mixtur (4) gaussian (2) network (2) textur (2) neural (2) featur (2) model (2) probabilist (1) handwritten (1) workaround (1)

## Person: Jiri Grim

### DBLP: Grim:Jiri

### Contributed to:

### Wrote 8 papers:

- ICPR-2010-SomolGP #algorithm #feature model #problem #set
- The Problem of Fragile Feature Subset Preference in Feature Selection Methods and a Proposal of Algorithmic Workaround (PS, JG, PP), pp. 4396–4399.
- MLDM-2007-GrimH #analysis #category theory #clustering
- Minimum Information Loss Cluster Analysis for Categorical Data (JG, JH), pp. 233–247.
- ICPR-v2-2006-GrimHSP #approach #modelling #using
- A Subspace Approach to Texture Modelling by Using Gaussian Mixtures (JG, MH, PS, PP), pp. 235–238.
- ICPR-v3-2004-HaindlGSPK
- A Gaussian Mixture-Based Colour Texture Model (MH, JG, PS, PP, MK), pp. 177–180.
- ICPR-v2-2002-GrimPS #network #probability
- Boosting in Probabilistic Neural Networks (JG, PP, PS), pp. 136–139.
- ICPR-v2-2000-GrimPS #multi #recognition
- Multivariate Structural Bernoulli Mixtures for Recognition of Handwritten Numerals (JG, PP, PS), pp. 2585–2589.
- ICPR-1998-GrimNPSF
- Initializing normal mixtures of densities (JG, JN, PP, PS, FJF), pp. 886–890.
- ICPR-1996-Grim #design #network
- Maximum-likelihood design of layered neural networks (JG), pp. 85–89.