Automatic Pavement Defect Detection and Classification Using RGB-Thermal Images Based on Hierarchical Residual Attention Network

A convolutional neural network based on an improved residual structure is proposed to implement a lightweight classification model for the recognition of complex pavement conditions, which uses RGB-thermal as input and embeds an attention module to adjust the spatial, as well as channel, information...

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Detalles Bibliográficos
Autores principales: Chen, Cheng, Chandra, Sindhu, Seo, Hyungjoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370849/
https://www.ncbi.nlm.nih.gov/pubmed/35957336
http://dx.doi.org/10.3390/s22155781

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370849/
https://www.ncbi.nlm.nih.gov/pubmed/35957336
http://dx.doi.org/10.3390/s22155781

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