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» On Feature Extraction via Kernels
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ICCV
2011
IEEE
12 years 10 months 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
BMCBI
2010
159views more  BMCBI 2010»
13 years 10 months ago
Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines
Background: Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods ha...
Alvaro J. González, Li Liao
ICCV
2007
IEEE
14 years 12 months ago
Feature Preserving Image Smoothing Using a Continuous Mixture of Tensors
Many computer vision and image processing tasks require the preservation of local discontinuities, terminations and bifurcations. Denoising with feature preservation is a challeng...
Özlem N. Subakan, Bing Jian, Baba C. Vemuri, ...
AVSS
2007
IEEE
14 years 4 months ago
Vehicular traffic density estimation via statistical methods with automated state learning
This paper proposes a novel approach of combining an unsupervised clustering scheme called AutoClass with Hidden Markov Models (HMMs) to determine the traffic density state in a R...
Evan Tan, Jing Chen
ACL
2004
13 years 11 months ago
The Sentimental Factor: Improving Review Classification Via Human-Provided Information
Sentiment classification is the task of labeling a review document according to the polarity of its prevailing opinion (favorable or unfavorable). In approaching this problem, a m...
Philip Beineke, Trevor Hastie, Shivakumar Vaithyan...