Vector quantization with the vq3 library

Thise page gather demos of the research I made on vector quantization. The demo use the C++ library vq3 available on my github. It is a muti-purpose library implementing efficiently vector quantization algoritms.

I published few papers on vector quantization (Frezza-Buet, 2020) (Frezza-Buet, 2014) (Frezza-Buet, 2008) (Drumea & Frezza-Buet, 2007), the recent ones rely on the vq3 library for the experimental content.

Publications

Drumea, G. A., & Frezza-Buet, H. (2007). Tracking fast changing non-stationary distributions with a topologically adaptive neural network: Application to video tracking. In 15th European Symposium on Artificial Neural Networks (ESANN2007) (pp. 43–48). Bruges, Belgium. Retrieved from https://hal-supelec.archives-ouvertes.fr/hal-00250981

Frezza-Buet, H. (2008). Following non-stationary distributions by controlling the vector quantization accuracy of a growing neural gas network. Neurocomputing, 71(7-9), 1191–1202. https://doi.org/10.1016/j.neucom.2007.12.024

Frezza-Buet, H. (2014). Online computing of non-stationary distributions velocity fields by an accuracy controlled growing neural gas. Neural Networks, 60, 203–221. https://doi.org/10.1016/j.neunet.2014.08.014

Frezza-Buet, H. (2020). Self-organizing maps in manifolds with complex topologies: An application to the planning of closed path for indoor UAV patrols. In European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, Belgium. Retrieved from https://hal.archives-ouvertes.fr/hal-02489649

Hervé Frezza-Buet,