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» A comparative study of two object recognition methods
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154
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CVPR
2009
IEEE
16 years 10 months ago
Learning Invariant Features Through Topographic Filter Maps
Several recently-proposed architectures for highperformance object recognition are composed of two main stages: a feature extraction stage that extracts locallyinvariant feature...
Koray Kavukcuoglu, Marc'Aurelio Ranzato, Rob Fergu...
131
Voted
ICMLA
2004
15 years 5 months ago
Two new regularized AdaBoost algorithms
AdaBoost rarely suffers from overfitting problems in low noise data cases. However, recent studies with highly noisy patterns clearly showed that overfitting can occur. A natural s...
Yijun Sun, Jian Li, William W. Hager
147
Voted
IISWC
2008
IEEE
15 years 10 months ago
PARSEC vs. SPLASH-2: A quantitative comparison of two multithreaded benchmark suites on Chip-Multiprocessors
The PARSEC benchmark suite was recently released and has been adopted by a significant number of users within a short amount of time. This new collection of workloads is not yet ...
Christian Bienia, Sanjeev Kumar, Kai Li
242
Voted
EJASMP
2011
14 years 7 months ago
Phoneme and Sentence-Level Ensembles for Speech Recognition
We address the question of whether and how boosting and bagging can be used for speech recognition. In order to do this, we compare two different boosting schemes, one at the pho...
Christos Dimitrakakis, Samy Bengio
153
Voted
FGR
2008
IEEE
180views Biometrics» more  FGR 2008»
15 years 3 months ago
Person-specific face recognition in unconstrained environments: a combination of offline and online learning
This paper studies face recognition and person-specific face image retrieval in unconstrained environments. The proposed method consists of two parts: offline and online learning....
Bangpeng Yao, Haizhou Ai, Shihong Lao