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Sensor Fusion
Beverages • Vol 8 • No 4
Exploration of Data Fusion Strategies Using Principal Component Analysis and Multiple Factor Analysis
2022
In oenology, statistical analyses are used for descriptive purposes, mostly with separate sensory and chemistry data sets. Cases that combine them are mostly supervised, usually seeking to optimize discrimination, classification, or prediction power. Unsuperv…
Article

Sensor Fusion

Combining of sensor data from disparate sources

Sensor fusion is the process of combining sensor data or data derived from disparate sources such that the resulting information has less uncertainty than would be possible when these sources were used individually. For instance, one could potentially obtain a more accurate location estimate of an indoor object by combining multiple data sources such as video cameras and WiFi localization signals. The term uncertainty reduction in this case can mean more accurate, more complete, or more dependable, or refer to the result of an emerging view, such as stereoscopic vision (calculation of depth information by combining two-dimensional images from two cameras at slightly different viewpoints).

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Beverages • Vol 8 • No 4
Exploration of Data Fusion Strategies Using Principal Component Analysis and Multiple Factor Analysis
2022
In oenology, statistical analyses are used for descriptive purposes, mostly with separate sensory and chemistry data sets. Cases that combine them are mostly supervised, usually seeking to optimize discrimination, classification, or prediction power. Unsupervised methods are used as preliminary steps to achieving success in supervised models. However, there is potential for unsupervised methods to combine different data sets into comprehensive, information-rich models. This study detailed stepwise strategies for c…
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Principal Component Analysis
Computer Science
Artificial Intelligence
Data Mining
Machine Learning
Mathematics
Combinatorics