Keywords
Affiliated Institutions
Related Publications
Graph embedding and extensions: a general framework for dimensionality reduction.
Over the past few decades, a large family of algorithms - supervised or unsupervised; stemming from statistics or geometry theory - has been designed to provide different soluti...
Learning Eigenfunctions Links Spectral Embedding and Kernel PCA
In this letter, we show a direct relation between spectral embedding methods and kernel principal components analysis and how both are special cases of a more general learning p...
Image Super-Resolution Via Sparse Representation
This paper presents a new approach to single-image super-resolution, based on sparse signal representation. Research on image statistics suggests that image patches can be well-...
A general framework for object detection
This paper presents a general trainable framework for object detection in static images of cluttered scenes. The detection technique we develop is based on a wavelet representat...
Publication Info
- Year
- 2007
- Type
- book-chapter
- Pages
- 352-363
- Citations
- 16
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1007/978-3-540-74260-9_32