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CVPR
2008
IEEE
16 years 5 months ago
A mixed generative-discriminative framework for pedestrian classification
This paper presents a novel approach to pedestrian classification which involves utilizing the synthesized virtual samples of a learned generative model to enhance the classificat...
Markus Enzweiler, Dariu M. Gavrila
AVSS
2006
IEEE
15 years 7 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
ECML
2006
Springer
15 years 7 months ago
Active Learning with Irrelevant Examples
Abstract. Active learning algorithms attempt to accelerate the learning process by requesting labels for the most informative items first. In real-world problems, however, there ma...
Dominic Mazzoni, Kiri Wagstaff, Michael C. Burl
ICML
2008
IEEE
16 years 4 months ago
ManifoldBoost: stagewise function approximation for fully-, semi- and un-supervised learning
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...
CIARP
2009
Springer
15 years 7 months ago
Pigmented Skin Lesions Classification Using Dermatoscopic Images
In this paper we propose a machine learning approach to classify melanocytic lesions in malignant and benign from dermatoscopic images. The image database is composed of 433 benign...
Germán Capdehourat, Andrés Corez, An...