2024-03-28T12:42:34Zhttps://gredos.usal.es/oai/requestoai:gredos.usal.es:10366/1351722024-03-12T12:40:14Zcom_10366_122575com_10366_4512com_10366_3823col_10366_156515
Automatic Prediction of Poisonous Mushrooms by Connectionist Systems
Navarro Cáceres, María
González Arrieta, María Angélica
De Paz , Juan F.
Bajo Pérez, Javier
Rodríguez González, Sara
Computer Science
The research offers a quite simple view of methods to classify edible and poisonous mushrooms. In fact, we are looking for not only classification methods but also for an application which supports experts’ decisions. To achieve our aim, we will study different structures of neural nets and learning algorithms, and select the best one, according to the test results.
2017-09-06T09:17:16Z
2017-09-06T09:17:16Z
2013/05
info:eu-repo/semantics/article
10th International Symposium on Distributed Computing and Artificial Intelligence (DCAI 2013). Advances in Intelligent Systems and Computing. Volumen 217, pp. 341-349.
978-3-319-00550-8(Print) / 978-3-319-00551-5(Online)
2194-5357(Print) / 2194-5365(Online)
http://dx.doi.org/10.1007/978-3-319-00551-5_42
http://hdl.handle.net/10366/135172
en
Attribution-NonCommercial-NoDerivs 3.0 Unported
https://creativecommons.org/licenses/by-nc-nd/3.0/
info:eu-repo/semantics/openAccess
application/pdf
Springer Science + Business Media