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CIVR
2003
Springer
107views Image Analysis» more  CIVR 2003»
14 years 17 days ago
Fast Video Retrieval under Sparse Training Data
Feature selection for video retrieval applications is impractical with existing techniques, because of their high time complexity and their failure on the relatively sparse trainin...
Yan Liu, John R. Kender
SODA
2008
ACM
127views Algorithms» more  SODA 2008»
13 years 8 months ago
Nondecreasing paths in a weighted graph or: how to optimally read a train schedule
A travel booking office has timetables giving arrival and departure times for all scheduled trains, including their origins and destinations. A customer presents a starting city a...
Virginia Vassilevska
CMIG
2010
110views more  CMIG 2010»
13 years 2 months ago
Unsupervised SVM-based gridding for DNA microarray images
This paper presents a novel method for unsupervised DNA microarray gridding based on Support Vector Machines (SVMs). Each spot is a small region on the microarray surface where cha...
Dimitris G. Bariamis, Dimitris Maroulis, Dimitrios...
JSAC
2007
117views more  JSAC 2007»
13 years 7 months ago
Optimization of Training and Scheduling in the Non-Coherent SIMO Multiple Access Channel
— Channel state information (CSI) is important for achieving large rates in MIMO channels. However, in timevarying MIMO channels, there is a tradeoff between the time/energy spen...
Sugumar Murugesan, Elif Uysal-Biyikoglu, Philip Sc...
CVPR
2011
IEEE
13 years 3 months ago
Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds
Active learning and crowdsourcing are promising ways to efficiently build up training sets for object recognition, but thus far techniques are tested in artificially controlled ...
Sudheendra Vijayanarasimhan, Kristen Grauman