Mean shift, mode seeking, and clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1995
Abstract
This research paper explore the methodology and findings associated with IEEE Transactions on Pattern Analysis and Machine Intelligence. The study delves into the core aspects of the research field, providing significant data and citation impact. (Full abstract processing is available via the OpenAlex API).
Related Research
- Mean Shift Algorithm and its Application in Tracking of Objects 2006
- Application of Mean shift method in target tracking 2007
- Algorithm of Adaptive Kernel-Bandwidth for Mean-Shift Based on Boundary Force 2010
- Object Robust Tracking Based an Improved Adaptive Mean-Shift Method 2012
- Application of Non-Parametric Mean Shift Method to Computer Vision 2010
References
- Stochastic global optimization methods part I: Clustering methods 1987
- Statistical mechanics and phase transitions in clustering 1990
- Density Estimation with Confidence Sets Exemplified by Superclusters and Voids in the Galaxies 1990
- A modified Hough transform for lines 1985
- Conceptual Clustering in Knowledge Organization 1985