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» Evaluating algorithms that learn from data streams
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ISBI
2009
IEEE
16 years 2 months ago
Quantitative Comparison of Spot Detection Methods in Live-Cell Fluorescence Microscopy Imaging
In live-cell fluorescence microscopy imaging, quantitative analysis of biological image data generally involves the detection of many subresolution objects, appearing as diffract...
Ihor Smal, Marco Loog, Wiro J. Niessen, Erik H. W....
ML
2008
ACM
15 years 7 months ago
Discovering significant patterns
Pattern discovery techniques, such as association rule discovery, explore large search spaces of potential patterns to find those that satisfy some user-specified constraints. Due...
Geoffrey I. Webb
TSMC
2008
116views more  TSMC 2008»
15 years 7 months ago
Fuzzy Techniques for Subjective Workload-Score Modeling Under Uncertainties
This paper deals with the development of a computer model to estimate the subjective workload score of individuals by evaluating their heart-rate (HR) signals. The identification o...
Mohit Kumar, D. Arndt, Steffi Kreuzfeld, Kerstin T...
BTW
2009
Springer
127views Database» more  BTW 2009»
16 years 2 months ago
In-Network Detection of Anomaly Regions in Sensor Networks with Obstacles
: In the past couple of years, sensor networks have evolved to a powerful infrastructure component for monitoring and tracking events and phenomena in many application domains. An ...
Conny Franke, Marcel Karnstedt, Daniel Klan, Micha...
CIKM
2006
Springer
15 years 11 months ago
Improving novelty detection for general topics using sentence level information patterns
The detection of new information in a document stream is an important component of many potential applications. In this work, a new novelty detection approach based on the identif...
Xiaoyan Li, W. Bruce Croft