Object-Level Data Augmentation for Deep Learning-Based Obstacle Detection in Railways

Object-Level Data Augmentation for Deep Learning-Based Obstacle Detection in Railways

This paper presents a novel method for generation of synthetic images of obstacles on and near rail tracks over long-range distances. The main goal is to augment the dataset for autonomous obstacle detection (OD) in railways, by inclusion of synthetic images that reflect the specific need for long-r...

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Bibliographic Details
Main Authors: Marten Franke, Vaishnavi Gopinath, Danijela Ristić-Durrant, Kai Michels
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Applied Sciences
Subjects:
object detection
data augmentation
synthetic images
railway safety
long-range obstacle detection
Online Access:https://www.mdpi.com/2076-3417/12/20/10625

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