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» An Instance Selection Approach to Multiple Instance Learning
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CVPR
2011
IEEE
14 years 6 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
AAAI
1998
14 years 11 months ago
Learning to Extract Symbolic Knowledge from the World Wide Web
The World Wide Web is a vast source of information accessible to computers, but understandable only to humans. The goal of the research described here is to automatically create a...
Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew M...
ICDCS
2007
IEEE
15 years 1 months ago
uSense: A Unified Asymmetric Sensing Coverage Architecture for Wireless Sensor Networks
As a key approach to achieve energy efficiency in sensor networks, sensing coverage has been studied extensively. Researchers have designed many coverage protocols to provide vario...
Yu Gu, Joengmin Hwang, Tian He, David Hung-Chang D...
GIS
2010
ACM
14 years 8 months ago
Detecting nearly duplicated records in location datasets
The quality of a local search engine, such as Google and Bing Maps, heavily relies on its geographic datasets. Typically, these datasets are obtained from multiple sources, e.g., ...
Yu Zheng, Xixuan Fen, Xing Xie, Shuang Peng, James...
ECSQARU
2007
Springer
15 years 4 months ago
PADUA Protocol: Strategies and Tactics
In this paper we describe an approach to classifying objects in a domain where classifications are uncertain using a novel combination of argumentation and data mining. Classific...
Maya Wardeh, Trevor J. M. Bench-Capon, Frans Coene...