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3DIM
2011
IEEE
8 years 16 hour ago
Finding the Best Feature Detector-Descriptor Combination
Addressing the image correspondence problem by feature matching is a central part of computer vision and 3D inference from images. Consequently, there is a substantial amount of w...
Anders Lindbjerg Dahl, Henrik Aanæs, Kim Ste...
ICANN
2011
Springer
8 years 3 months ago
Transforming Auto-Encoders
The artiļ¬cial neural networks that are used to recognize shapes typically use one or more layers of learned feature detectors that produce scalar outputs. By contrast, the comput...
Geoffrey E. Hinton, Alex Krizhevsky, Sida D. Wang
PAMI
2002
112views more  PAMI 2002»
8 years 11 months ago
Recognizing Handwritten Digits Using Hierarchical Products of Experts
The product of experts learning procedure [1] can discover a set of stochastic binary features that constitute a nonlinear generative model of handwritten images of digits. The qua...
Guy Mayraz, Geoffrey E. Hinton
NIPS
2000
9 years 1 months ago
Rate-coded Restricted Boltzmann Machines for Face Recognition
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
Yee Whye Teh, Geoffrey E. Hinton
DAGSTUHL
2006
9 years 1 months ago
A System for Object Class Detection
A successful detection and classification system must have two properties: it should be general enough to compensate for intra-class variability and it should be specific enough to...
Daniela Hall
DGCI
2006
Springer
9 years 3 months ago
Improving Difference Operators by Local Feature Detection
Differential operators are required to compute several characteristics for continuous surfaces, as e.g. tangents, curvature, flatness, shape descriptors. We propose to replace diff...
Kristof Teelen, Peter Veelaert
CLOR
2006
9 years 3 months ago
A Sparse Object Category Model for Efficient Learning and Complete Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
Robert Fergus, Pietro Perona, Andrew Zisserman
ECCV
2006
Springer
10 years 1 months ago
Machine Learning for High-Speed Corner Detection
Abstract Where feature points are used in real-time frame-rate applications, a high-speed feature detector is necessary. Feature detectors such as SIFT (DoG), Harris and SUSAN are ...
Edward Rosten, Tom Drummond
CVPR
2005
IEEE
10 years 2 months ago
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
Robert Fergus, Pietro Perona, Andrew Zisserman
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