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Mean shift is a non-parametric feature-space mathematical analysis technique for locating the maxima of a density function, a so-called mode-seeking algorithm. Application domains include cluster analysis in computer vision and image processing.
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| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Mean shift | is a | non-parametric feature-space mathematical analysis technique for locating the maxima of a density function | 0.90 | text |
| Mean shift | related to Availability | Variants | 0.60 | section |
| Mean shift | related to Availability | ELKI | 0.60 | section |
| Mean shift | related to Availability | Java | 0.60 | section |
| Mean shift | related to Availability | ImageJ | 0.60 | section |
| Mean shift | related to Availability | Image | 0.60 | section |
| Mean shift | related to Availability | Efficient | 0.60 | section |
| Mean shift | related to Availability | OpenCV | 0.60 | section |
| Mean shift | related to Availability | MethodOrfeo | 0.60 | section |
| Mean shift | related to Availability | Numpy/Python | 0.60 | section |
| Mean shift | related to Clustering | Consider | 0.60 | section |
| Mean shift | related to Clustering | Assume | 0.60 | section |
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