A Dual Neural Architecture Combined SqueezeNet with OctConv for LiDAR Data Classification

Light detection and ranging (LiDAR) is a frequently used technique of data acquisition and it is widely used in diverse practical applications. In recent years, deep convolutional neural networks (CNNs) have shown their effectiveness for LiDAR-derived rasterized digital surface models (LiDAR-DSM) da...

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Detalles Bibliográficos
Autores principales: Wang, Aili, Wang, Minhui, Jiang, Kaiyuan, Cao, Mengqing, Iwahori, Yuji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891785/
https://www.ncbi.nlm.nih.gov/pubmed/31726726
http://dx.doi.org/10.3390/s19224927

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891785/
https://www.ncbi.nlm.nih.gov/pubmed/31726726
http://dx.doi.org/10.3390/s19224927

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