Trajectory-based and sound-based medical data clustering
Author:
Affiliation:
1. University of Palermo, Palermo and Venice, Italy
2. Ca' Foscari University of Venice, Venezia, Italy
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3535508.3545102
Reference5 articles.
1. Using the Sonification for Hardly Detectable Details in Medical Images
2. C. Genolini R. Ecochard M. Benghezal D. Driss S. Andrieu and F. Subtil. 2016. kmlShape: An Efficient Method to Cluster Longitudinal Data (Time-Series) According to Their Shapes. PlosOne (2016). C. Genolini R. Ecochard M. Benghezal D. Driss S. Andrieu and F. Subtil. 2016. kmlShape: An Efficient Method to Cluster Longitudinal Data (Time-Series) According to Their Shapes. PlosOne (2016).
3. Music and timbre segmentation by recursive constrained K-means clustering
4. A. Rogińska , K. Friedman , and H. Mohanraj . 2013. Exploring sonification for augmenting Brain scan data . In International Conference on Auditory Display. A. Rogińska, K. Friedman, and H. Mohanraj. 2013. Exploring sonification for augmenting Brain scan data. In International Conference on Auditory Display.
5. Real-time audio and visual display of the Coronavirus genome
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