Image Analysis of Mushroom Types Classification by Convolution Neural Networks

dc.contributor.authorJitdumrong Preechasuk
dc.contributor.authorOrawan Chaowalit
dc.contributor.authorFuangfar Pensiri
dc.contributor.authorPorawat Visutsak
dc.date.accessioned2025-03-10T07:36:31Z
dc.date.available2025-03-10T07:36:31Z
dc.date.issued2019
dc.description.abstractMushrooms are fungi. The edible mushrooms include nutritional content and health benefits. However, some mushroom species is toxic and contains poisonous substances that could cause illness and lead to death. Mushroom poisoning accounts for approximately 70% of natural poisoning and often causes death. However, there are only 30-50 poisonous species among the thousands of species found on earth, and of these, no more than 10 are fatally poisonous [1]. The main reason of eating poisonous mushrooms is the lack of knowledge and skill to classify the edible and poisonous mushrooms. Besides, the physical characteristics of mushrooms are similar. Therefore, this work focuses on the classification of 45 types of mushrooms. This work aims to reduce the number of illness persons whom are risk of exposure to toxic mushrooms. This work proposes a new model of classifying 45 types of mushrooms including edible and poisonous mushrooms by using a technique of Convolution Neural Networks. The proposed model was tested on both types of mushroom. It was trained to construct the CNN models and used the trained models to classify all types of mushroom. The proposed model gives the results of 0.78, 0.73 and 0.74 of precision, recall and F1 score, respectively. It concluded that the proposed model can classify types of mushroom image with efficiently and effectively. � 2019 ACM.
dc.identifier.citationACM International Conference Proceeding Series
dc.identifier.doi10.1145/3375959.3375982
dc.identifier.isbn978-145037263-3
dc.identifier.scopus2-s2.0-85090187346
dc.identifier.urihttps://repository.dusit.ac.th//handle/123456789/4876
dc.languageEnglish
dc.publisherAssociation for Computing Machinery
dc.rights.holderScopus
dc.subjectAnalysis of mushroom image
dc.subjectClassification of mushroom type
dc.subjectConvolution Neural Network
dc.subjectMushroom image
dc.subjectPoisonous mushroom
dc.titleImage Analysis of Mushroom Types Classification by Convolution Neural Networks
dc.typeConference paper
mods.location.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85090187346&doi=10.1145%2f3375959.3375982&partnerID=40&md5=54457cb236d827d0b01944a951844853
oaire.citation.endPage88
oaire.citation.startPage82
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