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TIT
2008
102views more  TIT 2008»
14 years 11 months ago
On Low-Complexity Maximum-Likelihood Decoding of Convolutional Codes
Abstract--This letter considers the average complexity of maximum-likelihood (ML) decoding of convolutional codes. ML decoding can be modeled as finding the most probable path take...
Jie Luo
CVPR
2000
IEEE
16 years 1 months ago
Towards Automatic Discovery of Object Categories
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Markus Weber, Max Welling, Pietro Perona
ECCV
2006
Springer
16 years 1 months ago
TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-class Object Recognition and Segmentation
Abstract. This paper proposes a new approach to learning a discriminative model of object classes, incorporating appearance, shape and context information efficiently. The learned ...
Jamie Shotton, John M. Winn, Carsten Rother, Anton...
SIGCSE
2009
ACM
137views Education» more  SIGCSE 2009»
16 years 13 days ago
The hidden injuries of overloading 'ADT'
commonly stated definition of abstract data type (ADT) is that it is a domain of values and the operations over that domain. So, for example, a language's built-in types, lik...
Duane Buck, David J. Stucki
SIGGRAPH
1999
ACM
15 years 4 months ago
Creating Generative Models from Range Images
We describe a new approach for creating concise high-level generative models from range images or other approximate representations of real objects. Using data from a variety of a...
Ravi Ramamoorthi, James Arvo