Cargando…
FieldSAFE: Dataset for Obstacle Detection in Agriculture
In this paper, we present a multi-modal dataset for obstacle detection in agriculture. The dataset comprises approximately 2 h of raw sensor data from a tractor-mounted sensor system in a grass mowing scenario in Denmark, October 2016. Sensing modalities include stereo camera, thermal camera, web ca...
Autores principales: | Kragh, Mikkel Fly, Christiansen, Peter, Laursen, Morten Stigaard, Larsen, Morten, Steen, Kim Arild, Green, Ole, Karstoft, Henrik, Jørgensen, Rasmus Nyholm |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5713196/ https://www.ncbi.nlm.nih.gov/pubmed/29120383 http://dx.doi.org/10.3390/s17112579 |
Ejemplares similares
-
Designing and Testing a UAV Mapping System for Agricultural Field Surveying
por: Christiansen, Martin Peter, et al.
Publicado: (2017) -
Multi-Modal Detection and Mapping of Static and Dynamic Obstacles in Agriculture for Process Evaluation
por: Korthals, Timo, et al.
Publicado: (2018) -
DeepAnomaly: Combining Background Subtraction and Deep Learning for Detecting Obstacles and Anomalies in an Agricultural Field
por: Christiansen, Peter, et al.
Publicado: (2016) -
Automated Detection and Recognition of Wildlife Using Thermal Cameras
por: Christiansen, Peter, et al.
Publicado: (2014) -
Robust Species Distribution Mapping of Crop Mixtures Using Color Images and Convolutional Neural Networks
por: Skovsen, Søren Kelstrup, et al.
Publicado: (2020)