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» Unsupervised Learning of Invariant Features Using Video
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IJCNN
2006
IEEE
13 years 11 months ago
In-Place Learning for Positional and Scale Invariance
— In-place learning is a biologically inspired concept, meaning that the computational network is responsible for its own learning. With in-place learning, there is no need for a...
Juyang Weng, Hong Lu, Tianyu Luwang, Xiangyang Xue
CVPR
2007
IEEE
14 years 7 months ago
Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition
We present an unsupervised method for learning a hierarchy of sparse feature detectors that are invariant to small shifts and distortions. The resulting feature extractor consists...
Marc'Aurelio Ranzato, Fu Jie Huang, Y-Lan Boureau,...
NECO
2002
94views more  NECO 2002»
13 years 5 months ago
Slow Feature Analysis: Unsupervised Learning of Invariances
Laurenz Wiskott, Terrence J. Sejnowski
SPIESR
2004
196views Database» more  SPIESR 2004»
13 years 6 months ago
Video mining using combinations of unsupervised and supervised learning techniques
We discuss the meaning and significance of the video mining problem, and present our work on some aspects of video mining. A simple definition of video mining is unsupervised disc...
Ajay Divakaran, Koji Miyahara, Kadir A. Peker, Reg...
ICDAR
2007
IEEE
13 years 11 months ago
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images
We describe an unsupervised learning algorithm for extracting sparse and locally shift-invariant features. We also devise a principled procedure for learning hierarchies of invari...
Marc'Aurelio Ranzato, Yann LeCun