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» Learning Models for Object Recognition
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ICML
2004
IEEE
16 years 4 months ago
Learning random walk models for inducing word dependency distributions
Many NLP tasks rely on accurately estimating word dependency probabilities P(w1|w2), where the words w1 and w2 have a particular relationship (such as verb-object). Because of the...
Kristina Toutanova, Christopher D. Manning, Andrew...
144
Voted
DCC
2008
IEEE
16 years 3 months ago
Object-Based Regions of Interest for Image Compression
A fully automated architecture for object-based region of interest (ROI) detection is proposed. ROI's are defined as regions containing user defined objects of interest, and ...
Sunhyoung Han, Nuno Vasconcelos
159
Voted
AVSS
2009
IEEE
15 years 6 months ago
Bayesian Bio-inspired Model for Learning Interactive Trajectories
—Automatic understanding of human behavior is an important and challenging objective in several surveillance applications. One of the main problems of this task consists in accur...
Alessio Dore, Carlo S. Regazzoni
156
Voted
NIPS
2004
15 years 4 months ago
Surface Reconstruction using Learned Shape Models
We consider the problem of geometrical surface reconstruction from one or several images using learned shape models. While humans can effortlessly retrieve 3D shape information, t...
Jan Erik Solem, Fredrik Kahl
163
Voted
AAAI
2011
14 years 3 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos