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CVPR
2009
IEEE
15 years 1 months ago
Learning Signs from Subtitles: A Weakly Supervised Approach to Sign Language Recognition
This paper introduces a fully-automated, unsupervised method to recognise sign from subtitles. It does this by using data mining to align correspondences in sections of videos. Bas...
Helen Cooper, Richard Bowden
ICML
2009
IEEE
14 years 8 months ago
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations
There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...
CVPR
2010
IEEE
13 years 8 months ago
Boosting for transfer learning with multiple sources
Transfer learning allows leveraging the knowledge of source domains, available a priori, to help training a classifier for a target domain, where the available data is scarce. Th...
Yi Yao, Gianfranco Doretto
ICASSP
2011
IEEE
12 years 11 months ago
Generic object recognition using automatic region extraction and dimensional feature integration utilizing multiple kernel learn
Recently, in generic object recognition research, a classification technique based on integration of image features is garnering much attention. However, with a classifying techn...
Toru Nakashika, Akira Suga, Tetsuya Takiguchi, Yas...
ICCV
2005
IEEE
14 years 9 months ago
Combining Generative Models and Fisher Kernels for Object Recognition
Learning models for detecting and classifying object categories is a challenging problem in machine vision. While discriminative approaches to learning and classification have, in...
Alex Holub, Max Welling, Pietro Perona