Hidden Markov Models with Kernel Density Estimation of Emission Probabilities and their Use in Activity Recognition

By Massimo Piccardi, Óscar Pérez. 2007

37 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Jan Skoglund
2. Alejandro Luebs
3. W. Kleijn
4. Quan Wang
5. Thomas C. Walters
6. Felicia S. C. Lim
7. Florian Stimberg
8. Jean-Marc Valin

In Computer Vision and Pattern Recognition

1. Jan Skoglund
2. W. Kleijn
3. Quan Wang
4. Thomas C. Walters
5. Felicia S. C. Lim
6. Florian Stimberg
7. Alejandro Luebs
8. Jean-Marc Valin

Citations in the corpus

• Wavenet Based Low Rate Speech Coding (2017, methodology): “Refined generative models such as ARMA, e.g., [9], and kernel density estimation (KDE) HMM, e.g., [10], can also be used.”