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210
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ICCV
2011
IEEE
14 years 17 days ago
Adaptive Deconvolutional Networks for Mid and High Level Feature Learning
We present a hierarchical model that learns image decompositions via alternating layers of convolutional sparse coding and max pooling. When trained on natural images, the layers ...
Matthew D. Zeiler, Graham W. Taylor, Rob Fergus
89
Voted
DICTA
2003
15 years 1 months ago
Extracting Boundaries from Images by Comparing Cooccurrence Matrices
Abstract. This paper describes methods of extracting region boundaries from the frames of an image sequence by combining information from spatial or temporal cooccurrence matrices ...
Astrit Rexhepi, Azriel Rosenfeld
97
Voted
BMCBI
2006
91views more  BMCBI 2006»
15 years 18 days ago
Cheminformatics methods for novel nanopore analysis of HIV DNA termini
Background: Channel current feature extraction methods, using Hidden Markov Models (HMMs) have been designed for tracking individual-molecule conformational changes. This informat...
Stephen Winters-Hilt, Matthew Landry, Mark Akeson,...
101
Voted
BMCBI
2008
193views more  BMCBI 2008»
15 years 20 days ago
Missing value imputation for microarray gene expression data using histone acetylation information
Background: It is an important pre-processing step to accurately estimate missing values in microarray data, because complete datasets are required in numerous expression profile ...
Qian Xiang, Xianhua Dai, Yangyang Deng, Caisheng H...
WWW
2009
ACM
15 years 7 months ago
StatSnowball: a statistical approach to extracting entity relationships
Traditional relation extraction methods require pre-specified relations and relation-specific human-tagged examples. Bootstrapping systems significantly reduce the number of tr...
Jun Zhu, Zaiqing Nie, Xiaojiang Liu, Bo Zhang, Ji-...