Applying Fully Convolutional Architectures for Semantic Segmentation of a Single Tree Species in Urban Environment on High Resolution UAV Optical Imagery

This study proposes and evaluates five deep fully convolutional networks (FCNs) for the semantic segmentation of a single tree species: SegNet, U-Net, FC-DenseNet, and two DeepLabv3+ variants. The performance of the FCN designs is evaluated experimentally in terms of classification accuracy and comp...

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Detalles Bibliográficos
Autores principales: Lobo Torres, Daliana, Queiroz Feitosa, Raul, Nigri Happ, Patrick, Elena Cué La Rosa, Laura, Marcato Junior, José, Martins, José, Olã Bressan, Patrik, Gonçalves, Wesley Nunes, Liesenberg, Veraldo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014541/
https://www.ncbi.nlm.nih.gov/pubmed/31968589
http://dx.doi.org/10.3390/s20020563

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7014541/
https://www.ncbi.nlm.nih.gov/pubmed/31968589
http://dx.doi.org/10.3390/s20020563

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