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NIPS
2008
15 years 5 months ago
Natural Image Denoising with Convolutional Networks
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Viren Jain, H. Sebastian Seung
PAMI
2007
217views more  PAMI 2007»
15 years 3 months ago
Discriminative Learning and Recognition of Image Set Classes Using Canonical Correlations
—We address the problem of comparing sets of images for object recognition, where the sets may represent variations in an object’s appearance due to changing camera pose and li...
Tae-Kyun Kim, Josef Kittler, Roberto Cipolla
BMCBI
2006
202views more  BMCBI 2006»
15 years 4 months ago
Spectral embedding finds meaningful (relevant) structure in image and microarray data
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
Brandon W. Higgs, Jennifer W. Weller, Jeffrey L. S...
DAGM
2001
Springer
15 years 9 months ago
3D Model Retrieval with Spherical Harmonics and Moments
We consider 3D object retrieval in which a polygonal mesh serves as a query and similar objects are retrieved from a collection of 3D objects. Algorithms proceed first by a normal...
Dietmar Saupe, Dejan V. Vranic
ICIP
2010
IEEE
15 years 2 months ago
A close-up detection method for movies
Close-up (CU) is a photographic technique which tightly frames a person or an object. In movies, it is applied to guide audience attention and to evoke audience emotion. In this p...
Huiying Liu, Min Xu, Qingming Huang, Jesse S. Jin,...