Peter Hviid Christiansen
Peter Hviid Christiansen
PhD, Department of Engineering, Aarhus University
Verified email at
Cited by
Cited by
Automated detection and recognition of wildlife using thermal cameras
P Christiansen, KA Steen, RN Jørgensen, H Karstoft
Sensors 14 (8), 13778-13793, 2014
DeepAnomaly: Combining background subtraction and deep learning for detecting obstacles and anomalies in an agricultural field
P Christiansen, LN Nielsen, KA Steen, RN Jørgensen, H Karstoft
Sensors 16 (11), 1904, 2016
Using deep learning to challenge safety standard for highly autonomous machines in agriculture
KA Steen, P Christiansen, H Karstoft, RN Jørgensen
Journal of Imaging 2 (1), 6, 2016
Fieldsafe: dataset for obstacle detection in agriculture
MF Kragh, P Christiansen, MS Laursen, M Larsen, KA Steen, O Green, ...
Sensors 17 (11), 2579, 2017
Estimation of plant species by classifying plants and leaves in combination
M Dyrmann, P Christiansen, HS Midtiby
Journal of Field Robotics 35 (2), 202-212, 2018
Unsuperpoint: End-to-end unsupervised interest point detector and descriptor
PH Christiansen, MF Kragh, Y Brodskiy, H Karstoft
arXiv preprint arXiv:1907.04011, 2019
Platform for evaluating sensors and human detection in autonomous mowing operations
P Christiansen, M Kragh, KA Steen, H Karstoft, RN Jørgensen
Precision agriculture 18 (3), 350-365, 2017
Advanced sensor platform for human detection and protection in autonomous farming
P Christiansen, MK Hansen, KA Steen, H Karstoft, RN Jørgensen
Precision agriculture'15, 1330-1334, 2015
Automated classification of seedlings using computer vision
M Dyrmann, P Christiansen
Aarhus University, School of Engineering, Technical Information Technology, 2014
Multi-modal detection and mapping of static and dynamic obstacles in agriculture for process evaluation
T Korthals, M Kragh, P Christiansen, H Karstoft, RN Jørgensen, U Rückert
Frontiers in Robotics and AI 5, 28, 2018
Multi-modal obstacle detection and evaluation of occupancy grid mapping in agriculture
M Kragh, P Christiansen, T Korthals, T Jungeblut, H Karstoft, ...
Proceedings of the International Conference on Agricultural Engineering …, 2016
Towards autonomous plant production using fully convolutional neural networks.
P Christiansen, R Sørensen, S Skovsen, CD Jæger, RN Jørgensen, ...
CIGR-AgEng Conference, 26-29 June 2016, Aarhus, Denmark. Abstracts and Full …, 2016
Towards inverse sensor mapping in agriculture
T Korthals, M Kragh, P Christiansen, U Rückert
arXiv preprint arXiv:1805.08595, 2018
Field trial design using semi-automated conventional machinery and aerial drone imaging for outlier identification
RN Jørgensen, MB Brandt, T Schmidt, MS Laursen, R Larsen, ...
Precision agriculture'15, 146-151, 2015
Towards a DSL for Perception-Based Safety Systems
JTM Ingibergsson, SD Suvei, MK Hansen, P Christiansen, UP Schultz
arXiv preprint arXiv:1603.01965, 2016
TractorEYE: Vision-based Real-time Detection for Autonomous Vehicles in Agriculture
P Christiansen
Department of Engineering, Aarhus University, 2017
Stereo and active-sensor data fusion for improved stereo block matching
SD Suvei, L Bodenhagen, L Kiforenko, P Christiansen, RN Jørgensen, ...
International Conference on Image Analysis and Recognition, 451-461, 2016
Sparse-to-Dense Depth Completion in Precision Farming
S Farkhani, MF Kragh, PH Christiansen, RN Jørgensen, H Karstoft
Proceedings of the 3rd International Conference on Vision, Image and Signal …, 2019
FieldSAFE: Dataset for Obstacle Detection in Agriculture
M Fly Kragh, P Christiansen, M Stigaard Laursen, M Larsen, K Arild Steen, ...
arXiv, arXiv: 1709.03526, 2017
Embedded Visual Perception for Autonomous Agricultural Machines Using Lightweight Convolutional Neural Networks
RA Sørensen, S Skovsen, P Christiansen, H Karstoft
ICSWTS 2017 11 (4), 2017
The system can't perform the operation now. Try again later.
Articles 1–20