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ML
1998
ACM
153views Machine Learning» more  ML 1998»
13 years 7 months ago
Bayesian Landmark Learning for Mobile Robot Localization
To operate successfully in indoor environments, mobile robots must be able to localize themselves. Most current localization algorithms lack flexibility, autonomy, and often optim...
Sebastian Thrun
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 7 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
CSREAPSC
2006
13 years 8 months ago
Sensor Network Lab Exercises Using TinyOS and MicaZ Motes
- MIT Technology Review lists sensor networks as one of "Ten Emerging Technologies That Will Change the World" [1]. This paper describes three lab exercises that are suit...
Jens Mache, Chris Allick, John Charnas, Alex Hickm...
INFOCOM
2007
IEEE
14 years 1 months ago
Optimal Policies for Distributed Data Aggregation in Wireless Sensor Networks
Abstract— We consider the scenario of distributed data aggregation in wireless sensor networks, where each sensor can obtain and estimate the information of the whole sensing fi...
Zhenzhen Ye, Alhussein A. Abouzeid, Jing Ai
BSN
2009
IEEE
140views Sensor Networks» more  BSN 2009»
14 years 2 months ago
A Distributed Hidden Markov Model for Fine-grained Annotation in Body Sensor Networks
—Human movement models often divide movements into parts. In walking the stride can be segmented into four different parts, and in golf and other sports, the swing is divided int...
Eric Guenterberg, Hassan Ghasemzadeh, Roozbeh Jafa...