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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...
Autores principales: | Mujkic, Esma, Philipsen, Mark P., Moeslund, Thomas B., Christiansen, Martin P., Ravn, Ole |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
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 |
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