Anomaly Detection for Agricultural Vehicles Using Autoencoders

The safe in-field operation of autonomous agricultural vehicles requires detecting all objects that pose a risk of collision. Current vision-based algorithms for object detection and classification are unable to detect unknown classes of objects. In this paper, the problem is posed as anomaly detect...

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Detalles Bibliográficos
Autores principales: Mujkic, Esma, Philipsen, Mark P., Moeslund, Thomas B., Christiansen, Martin P., Ravn, Ole
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9145690/
https://www.ncbi.nlm.nih.gov/pubmed/35632017
http://dx.doi.org/10.3390/s22103608

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9145690/
https://www.ncbi.nlm.nih.gov/pubmed/35632017
http://dx.doi.org/10.3390/s22103608

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