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NAACL
2003
15 years 2 months ago
Active Learning for Classifying Phone Sequences from Unsupervised Phonotactic Models
This paper describes an application of active learning methods to the classification of phone strings recognized using unsupervised phonotactic models. The only training data req...
Shona Douglas
CVPR
2010
IEEE
15 years 9 months ago
Learning from Interpolated Images using Neural Networks for Digital Forensics
Interpolated images have data redundancy, and special correlation exists among neighboring pixels, which is a crucial clue in digital forensics. We design a neural network based f...
Yizhen Huang, Na Fan
ICML
2009
IEEE
16 years 2 months ago
Learning kernels from indefinite similarities
Similarity measures in many real applications generate indefinite similarity matrices. In this paper, we consider the problem of classification based on such indefinite similariti...
Yihua Chen, Maya R. Gupta, Benjamin Recht
WACV
2005
IEEE
15 years 7 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
IFIP
2007
Springer
15 years 7 months ago
Lessons Learned from the Maroochy Water Breach
Supervisory control and data acquisition (SCADA) systems are widely used to monitor and control operations in electrical power distribution facilities, oil and gas pipelines, water...
Jill Slay, Michael Miller