TY - CHAP
T1 - Morphological neural networks with dendritic processing for pattern classification
AU - Sossa, Humberto
AU - Arce, Fernando
AU - Zamora, Erik
AU - Guevara, Elizabeth
N1 - Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018. All rights reserved.
PY - 2018/4/28
Y1 - 2018/4/28
N2 - 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.
AB - 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.
KW - Artificial intelligence
KW - Morphological neural networks with dendritic processing Pattern classification
UR - http://www.scopus.com/inward/record.url?scp=85060469853&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-77770-2_2
DO - 10.1007/978-3-319-77770-2_2
M3 - Capítulo
SN - 9783319777696
SP - 27
EP - 47
BT - Advanced Topics on Computer Vision, Control and Robotics in Mechatronics
PB - Springer International Publishing
ER -