Publicación:
DEEP LEARNING FOR CHILEAN NATIVE FLORA CLASSIFICATION: A COMPARATIVE ANALYSIS

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dc.creatorCAROLA ANDREA FIGUEROA FLORES
dc.date2023
dc.date.accessioned2025-01-10T15:41:53Z
dc.date.available2025-01-10T15:41:53Z
dc.date.issued2023
dc.description.abstractTHE LIMITED AVAILABILITY OF INFORMATION ON CHILEAN NATIVE FLORA HAS RESULTED IN A LACK OF KNOWLEDGE AMONG THE GENERAL PUBLIC, AND THE CLASSIFICATION OF THESE PLANTS POSES CHALLENGES WITHOUT EXTENSIVE EXPERTISE. THIS STUDY EVALUATES THE PERFORMANCE OF SEVERAL DEEP LEARNING (DL) MODELS, NAMELY INCEPTIONV3, VGG19, RESNET152, AND MOBILENETV2, IN CLASSIFYING IMAGES REPRESENTING CHILEAN NATIVE FLORA. THE MODELS ARE PRE-TRAINED ON IMAGENET. A DATASET CONTAINING 500 IMAGES FOR EACH OF THE 10 CLASSES OF NATIVE FLOWERS IN CHILE WAS CURATED, RESULTING IN A TOTAL OF 5000 IMAGES. THE DL MODELS WERE APPLIED TO THIS DATASET, AND THEIR PERFORMANCE WAS COMPARED BASED ON ACCURACY AND OTHER RELEVANT METRICS. THE FINDINGS HIGHLIGHT THE POTENTIAL OF DL MODELS TO ACCURATELY CLASSIFY IMAGES OF CHILEAN NATIVE FLORA. THE RESULTS CONTRIBUTE TO ENHANCING THE UNDERSTANDING OF THESE PLANT SPECIES AND FOSTERING AWARENESS AMONG THE GENERAL PUBLIC. FURTHER IMPROVEMENTS AND APPLICATIONS OF DL IN ECOLOGY AND BIODIVERSITY RESEARCH ARE DISCUSSED.
dc.formatapplication/pdf
dc.identifier.doi10.3389/fpls.2023.1211490
dc.identifier.issn1664-462X
dc.identifier.issn1664-462X
dc.identifier.urihttps://repositorio.ubiobio.cl/handle/123456789/13239
dc.languagespa
dc.publisherFrontiers in Plant Science
dc.relation.uri10.3389/fpls.2023.1211490
dc.rightsPUBLICADA
dc.subjecttransfer learning
dc.subjectimage classification
dc.subjectdeep learning
dc.subjectconvolutional neural network
dc.subjectChilean native flora
dc.titleDEEP LEARNING FOR CHILEAN NATIVE FLORA CLASSIFICATION: A COMPARATIVE ANALYSIS
dc.typeARTÍCULO
dspace.entity.typePublication
ubb.EstadoPUBLICADA
ubb.Otra ReparticionDEPARTAMENTO DE CIENCIAS DE LA COMPUTACION Y TECNOLOGIA DE LA INFORMACION.
ubb.SedeCHILLÁN
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