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» Objective Functions for Feature Discrimination
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SSPR
2010
Springer
14 years 11 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
ICASSP
2011
IEEE
14 years 4 months ago
Soft frame margin estimation of Gaussian Mixture Models for speaker recognition with sparse training data
—Discriminative Training (DT) methods for acoustic modeling, such as MMI, MCE, and SVM, have been proved effective in speaker recognition. In this paper we propose a DT method fo...
Yan Yin, Qi Li
84
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EVOW
2003
Springer
15 years 5 months ago
Pixel Statistics and False Alarm Area in Genetic Programming for Object Detection
This paper describes a domain independent approach to the use of genetic programming for object detection problems. Rather than using raw pixels or high level domain specific feat...
Mengjie Zhang, Peter Andreae, Mark Pritchard
PVLDB
2008
82views more  PVLDB 2008»
15 years 4 hour ago
TraClass: trajectory classification using hierarchical region-based and trajectory-based clustering
Trajectory classification, i.e., model construction for predicting the class labels of moving objects based on their trajectories and other features, has many important, real-worl...
Jae-Gil Lee, Jiawei Han, Xiaolei Li, Hector Gonzal...
ECCV
2004
Springer
16 years 2 months ago
Weak Hypotheses and Boosting for Generic Object Detection and Recognition
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...