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» A Discriminative Framework for Modelling Object Classes
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ACCV
2006
Springer
15 years 5 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
15 years 3 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
14 years 10 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»
16 years 6 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»
14 years 6 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