Morphological neural networks, in particular, those with dendritic processing (MNNDPs), have shown to be a very promising tool for pattern classification. In this chapter, we present a survey of the most recent advances concerning MNNDPs. We provide the basics of each model and training algorithm; in some cases, we present simple examples to facilitate the understanding of the material. In all cases, we compare the described models with some of the state-of-the-art counterparts to demonstrate the advantages and disadvantages. In the end, we present a summary and a series of conclusions and trends for present and further research.
CITATION STYLE
Sossa, H., Arce, F., Zamora, E., & Guevara, E. (2018). Morphological neural networks with dendritic processing for pattern classification. In Advanced Topics on Computer Vision, Control and Robotics in Mechatronics (pp. 27–47). Springer International Publishing. https://doi.org/10.1007/978-3-319-77770-2_2
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