Anomaly Detection for Agricultural Vehicles Using Autoencoders

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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Bibliographic Details
Main Authors: Esma Mujkic, Mark P. Philipsen, Thomas B. Moeslund, Martin P. Christiansen, Ole Ravn
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Sensors
Subjects:
anomaly detection
agricultural vehicle
autoencoder
deep learning
computer vision
Online Access:https://www.mdpi.com/1424-8220/22/10/3608

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https://www.mdpi.com/1424-8220/22/10/3608

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