Automatic identification of charcoal origin based on deep learning
Abstract: The differentiation between the charcoal produced from (Eucalyptus) plantations and native forests is essential to control, commercialization, and supervision of its production in Brazil. The main contribution of this study is to identify the charcoal origin using macroscopic images and De...
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| Lenguaje: | English |
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Universidad del Bío-Bío
2021
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oai:scielo:S0718-221X20210001004652021-10-05Automatic identification of charcoal origin based on deep learningRodrigues de Oliveira Neto,RicardoFerreira Rodrigues,LarissaMari,João FernandoCoelho Naldi,MuriloGomes Milagres,EmersonRocha Vital,BeneditoOliveira Carneiro,Angélica de CássiaBreda Binoti,Daniel HenriqueLopes,Pablo FalcoGarcia Leite,Helio Charcoal classification deep learning native wood preprocessing. Abstract: The differentiation between the charcoal produced from (Eucalyptus) plantations and native forests is essential to control, commercialization, and supervision of its production in Brazil. The main contribution of this study is to identify the charcoal origin using macroscopic images and Deep Learning Algorithm. We applied a Convolutional Neural Network (CNN) using VGG-16 architecture, with preprocessing based on contrast enhancement and data augmentation with rotation over the training set images. on the performance of the CNN with fine-tuning using 360 macroscopic charcoal images from the plantation and native forests. The results pointed out that our method provides new perspectives to identify the charcoal origin, achieving results upper 95 % of mean accuracy to classify charcoal from native forests for all compared preprocessing strategies.info:eu-repo/semantics/openAccessUniversidad del Bío-BíoMaderas. Ciencia y tecnología v.23 20212021-01-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2021000100465en10.4067/s0718-221x2021000100465 |
| institution |
Scielo Chile |
| collection |
Scielo Chile |
| language |
English |
| topic |
Charcoal classification deep learning native wood preprocessing. |
| spellingShingle |
Charcoal classification deep learning native wood preprocessing. Rodrigues de Oliveira Neto,Ricardo Ferreira Rodrigues,Larissa Mari,João Fernando Coelho Naldi,Murilo Gomes Milagres,Emerson Rocha Vital,Benedito Oliveira Carneiro,Angélica de Cássia Breda Binoti,Daniel Henrique Lopes,Pablo Falco Garcia Leite,Helio Automatic identification of charcoal origin based on deep learning |
| description |
Abstract: The differentiation between the charcoal produced from (Eucalyptus) plantations and native forests is essential to control, commercialization, and supervision of its production in Brazil. The main contribution of this study is to identify the charcoal origin using macroscopic images and Deep Learning Algorithm. We applied a Convolutional Neural Network (CNN) using VGG-16 architecture, with preprocessing based on contrast enhancement and data augmentation with rotation over the training set images. on the performance of the CNN with fine-tuning using 360 macroscopic charcoal images from the plantation and native forests. The results pointed out that our method provides new perspectives to identify the charcoal origin, achieving results upper 95 % of mean accuracy to classify charcoal from native forests for all compared preprocessing strategies. |
| author |
Rodrigues de Oliveira Neto,Ricardo Ferreira Rodrigues,Larissa Mari,João Fernando Coelho Naldi,Murilo Gomes Milagres,Emerson Rocha Vital,Benedito Oliveira Carneiro,Angélica de Cássia Breda Binoti,Daniel Henrique Lopes,Pablo Falco Garcia Leite,Helio |
| author_facet |
Rodrigues de Oliveira Neto,Ricardo Ferreira Rodrigues,Larissa Mari,João Fernando Coelho Naldi,Murilo Gomes Milagres,Emerson Rocha Vital,Benedito Oliveira Carneiro,Angélica de Cássia Breda Binoti,Daniel Henrique Lopes,Pablo Falco Garcia Leite,Helio |
| author_sort |
Rodrigues de Oliveira Neto,Ricardo |
| title |
Automatic identification of charcoal origin based on deep learning |
| title_short |
Automatic identification of charcoal origin based on deep learning |
| title_full |
Automatic identification of charcoal origin based on deep learning |
| title_fullStr |
Automatic identification of charcoal origin based on deep learning |
| title_full_unstemmed |
Automatic identification of charcoal origin based on deep learning |
| title_sort |
automatic identification of charcoal origin based on deep learning |
| publisher |
Universidad del Bío-Bío |
| publishDate |
2021 |
| url |
http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-221X2021000100465 |
| work_keys_str_mv |
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