Travelled to:1 × Austria
1 × Canada
1 × Spain
1 × Sweden
1 × Turkey
1 × USA
Collaborated with:A.Zare J.Bolton S.E.Yuksel R.Mazhar ∅ J.Liu N.Theera-Umpon J.Chiang H.Jenzri H.Frigui
Talks about:recognit (3) framework (2) function (2) pattern (2) network (2) multipl (2) instanc (2) detect (2) optim (2) count (2)
Person: Paul D. Gader
DBLP: Gader:Paul_D=
Contributed to:
201420102008200220001996Wrote 10 papers:
- ICPR-2014-JenzriFG #robust
- Robust Context Dependent Spectral Unmixing (HJ, HF, PDG), pp. 643–647.
- ICPR-2010-BoltonG #framework #learning #multi #optimisation #random #set
- Cross Entropy Optimization of the Random Set Framework for Multiple Instance Learning (JB, PDG), pp. 3907–3910.
- ICPR-2010-YukselG #classification #detection
- Variational Mixture of Experts for Classification with Applications to Landmine Detection (SEY, PDG), pp. 2981–2984.
- ICPR-2010-ZareG #multi #pattern matching #pattern recognition #recognition #using
- Pattern Recognition Using Functions of Multiple Instances (AZ, PDG), pp. 1092–1095.
- ICPR-2008-MazharG #design #named #taxonomy
- EK-SVD: Optimized dictionary design for sparse representations (RM, PDG), pp. 1–4.
- ICPR-2008-ZareG #detection #process #using
- Endmember detection using the Dirichlet process (AZ, PDG), pp. 1–4.
- ICPR-v2-2002-Gader #pattern matching #pattern recognition #recognition
- Pattern Recognition for Humanitarian De-mining (PDG), pp. 521–522.
- ICPR-v2-2000-LiuG #network
- Outlier Rejection with MLPs and Variants of RBF Networks (JL, PDG), pp. 2680–2683.
- ICPR-v2-2000-Theera-UmponG #fault #network
- Training Neural Networks to Count White Blood Cells via a Minimum Counting Error Objective Function (NTU, PDG), pp. 2299–2302.
- ICPR-1996-ChiangG #feature model #framework #hybrid #recognition
- A hybrid feature extraction framework for handwritten numeric fields recognition (JHC, PDG), pp. 436–440.