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» A Discriminative Framework for Modelling Object Classes
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ACCV
2006
Springer
14 years 3 months ago
Probabilistic Modeling for Structural Change Inference
We view the task of change detection as a problem of object recognition from learning. The object is defined in a 3D space where the time is the 3rd dimension. We propose two com...
Wei Liu, Véronique Prinet
GI
1997
Springer
14 years 1 months ago
Functional Object-Oriented Programming with Object-Gofer
Object-Gofer is a small, practical extension of the functional programming language Gofer incorporating the following ideas from the object-oriented community: objects and toplevel...
Wolfram Schulte, Klaus Achatz
SSPR
2010
Springer
13 years 7 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...
CVPR
2009
IEEE
1002views Computer Vision» more  CVPR 2009»
15 years 4 months ago
Classifier Grids for Robust Adaptive Object Detection
In this paper we present an adaptive but robust object detector for static cameras by introducing classifier grids. Instead of using a sliding window for object detection we pro...
Peter M. Roth, Sabine Sternig, Helmut Grabner, Hor...
TNN
2010
234views Management» more  TNN 2010»
13 years 3 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes