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» Coarse-to-Fine Object Recognition Using Shock Graphs
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ICASSP
2010
IEEE
14 years 12 months ago
Large margin estimation of n-gram language models for speech recognition via linear programming
We present a novel discriminative training algorithm for n-gram language models for use in large vocabulary continuous speech recognition. The algorithm uses large margin estimati...
Vladimir Magdin, Hui Jiang
DAGM
2008
Springer
15 years 1 months ago
MAP-Inference for Highly-Connected Graphs with DC-Programming
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
Jörg H. Kappes, Christoph Schnörr
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
16 years 3 days ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
ICDAR
2007
IEEE
15 years 6 months ago
Energy-Based Models in Document Recognition and Computer Vision
The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
Yann LeCun, Sumit Chopra, Marc'Aurelio Ranzato, Fu...
IBPRIA
2005
Springer
15 years 5 months ago
From Moving Edges to Moving Regions
In this paper, we propose a new method to extract moving objects from a video stream without any motion estimation. The objective is to obtain a method robust to noise, large motio...
Loic Biancardini, Eva Dokladalova, Serge Beucher, ...