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WSOM
2009
Springer
14 years 4 months ago
Incremental Figure-Ground Segmentation Using Localized Adaptive Metrics in LVQ
Vector quantization methods are confronted with a model selection problem, namely the number of prototypical feature representatives to model each class. In this paper we present a...
Alexander Denecke, Heiko Wersing, Jochen J. Steil,...
CORR
2011
Springer
222views Education» more  CORR 2011»
13 years 1 months ago
Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
Abstract. We propose an extension of the Restricted Boltzmann Machine (RBM) that allows the joint shape and appearance of foreground objects in cluttered images to be modeled indep...
Nicolas Heess, Nicolas Le Roux, John M. Winn
CVPR
2009
IEEE
15 years 5 months ago
Towards Total Scene Understanding: Classification, Annotation and Segmentation in an Automatic Framework
Given an image, we propose a hierarchical generative model that classifies the overall scene, recognizes and segments each object component, as well as annotates the image with ...
Fei-Fei Li 0002, Li-Jia Li, Richard Socher
EMNLP
2009
13 years 8 months ago
Supervised Learning of a Probabilistic Lexicon of Verb Semantic Classes
The work presented in this paper explores a supervised method for learning a probabilistic model of a lexicon of VerbNet classes. We intend for the probabilistic model to provide ...
Yusuke Miyao, Jun-ichi Tsujii
CLOUD
2010
ACM
14 years 3 months ago
Nephele/PACTs: a programming model and execution framework for web-scale analytical processing
We present a parallel data processor centered around a programming model of so called Parallelization Contracts (PACTs) and the scalable parallel execution engine Nephele [18]. Th...
Dominic Battré, Stephan Ewen, Fabian Hueske...