DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field

DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field

Convolutional neural network (CNN)-based systems are increasingly used in autonomous vehicles for detecting obstacles. CNN-based object detection and per-pixel classification (semantic segmentation) algorithms are trained for detecting and classifying a predefined set of object types. These algorith...

Full description

Bibliographic Details
Main Authors: Peter Christiansen, Lars N. Nielsen, Kim A. Steen, Rasmus N. Jørgensen, Henrik Karstoft
Format: Article
Language:English
Published: MDPI AG 2016-11-01
Series:Sensors
Subjects:
anomaly detection
obstacle detection
autonomous farming
precision agriculture
camera
background subtraction
change detection
DeepAnomaly
Online Access:http://www.mdpi.com/1424-8220/16/11/1904

Internet

http://www.mdpi.com/1424-8220/16/11/1904

Similar Items