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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
IDEAL
2009
Springer
13 years 8 months ago
Optimizing Data Transformations for Classification Tasks
Many classification algorithms use the concept of distance or similarity between patterns. Previous work has shown that it is advantageous to optimize general Euclidean distances (...
José María Valls, Ricardo Aler
CVPR
2008
IEEE
15 years 11 days ago
Kernel-based learning of cast shadows from a physical model of light sources and surfaces for low-level segmentation
In background subtraction, cast shadows induce silhouette distortions and object fusions hindering performance of high level algorithms in scene monitoring. We introduce a nonpara...
André Zaccarin, Nicolas Martel-Brisson
ECCV
2008
Springer
15 years 7 days ago
Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...
Cassio Polpo de Campos, Yan Tong, Qiang Ji
CHI
2001
ACM
14 years 10 months ago
Locus of feedback control in computer-based tutoring: impact on learning rate, achievement and attitudes
The advent of second-generation intelligent computer tutors raises an important instructional design question: when should tutorial advice be presented in problem solving? This pa...
Albert T. Corbett, John R. Anderson