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» Using Data Mining to Estimate Missing Sensor Data
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TSP
2008
117views more  TSP 2008»
15 years 5 months ago
Sample Eigenvalue Based Detection of High-Dimensional Signals in White Noise Using Relatively Few Samples
The detection and estimation of signals in noisy, limited data is a problem of interest to many scientific and engineering communities. We present a mathematically justifiable, com...
R. R. Nadakuditi, A. Edelman
MM
2010
ACM
200views Multimedia» more  MM 2010»
15 years 6 months ago
Multimodal location estimation
In this article we define a multimedia content analysis problem, which we call multimodal location estimation: Given a video/image/audio file, the task is to determine where it wa...
Gerald Friedland, Oriol Vinyals, Trevor Darrell
SENSYS
2003
ACM
15 years 11 months ago
On the scaling laws of dense wireless sensor networks
We consider dense wireless sensor networks deployed to observe arbitrary random fields. The requirement is to reconstruct an estimate of the random field at a certain collector ...
Praveen Kumar Gopala, Hesham El Gamal
IBERAMIA
2004
Springer
15 years 11 months ago
Statistical Inference in Mapping and Localization for Mobile Robots
In this paper we tackle the problem of providing a mobile robot with the ability to build a map of its environment using data gathered during navigation. The data correspond to the...
Anita Araneda, Alvaro Soto
SPEECH
2010
136views more  SPEECH 2010»
15 years 4 months ago
Robust speech recognition by integrating speech separation and hypothesis testing
Missing data methods attempt to improve robust speech recognition by distinguishing between reliable and unreliable data in the time-frequency domain. Such methods require a binar...
Soundararajan Srinivasan, DeLiang L. Wang