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» A Probability Model for Image Annotation
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MICCAI
2007
Springer
15 years 8 months ago
Robust Autonomous Model Learning from 2D and 3D Data Sets
In this paper we propose a weakly supervised learning algorithm for appearance models based on the minimum description length (MDL) principle. From a set of training images or volu...
Georg Langs, Rene Donner, Philipp Peloschek, Horst...
ICPR
2010
IEEE
14 years 12 months ago
Boosting Bayesian MAP Classification
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
Paolo Piro, Richard Nock, Frank Nielsen, Michel Ba...
SCALESPACE
2007
Springer
15 years 8 months ago
Uniform and Textured Regions Separation in Natural Images Towards MPM Adaptive Denoising
Abstract. Natural images consist of texture, structure and smooth regions and this makes the task of filtering challenging mainly when it aims at edge and texture preservation. In...
Noura Azzabou, Nikos Paragios, Frederic Guichard
ICCV
1995
IEEE
15 years 5 months ago
Closed-World Tracking
A new approach to tracking weakly modeled objects in a semantically rich domain is presented. We define a closed-world as a space-time region of an image sequence in which the co...
Stephen S. Intille, Aaron F. Bobick
CVPR
2010
IEEE
15 years 10 months ago
Breaking the interactive bottleneck in multi-class classification with active selection and binary feedback
Multi-class classification schemes typically require human input in the form of precise category names or numbers for each example to be annotated – providing this can be impra...
Ajay Joshi, Fatih Porikli, Nikolaos Papanikolopoul...