Peter Hviid Christiansen
Peter Hviid Christiansen
PhD, Department of Engineering, Aarhus University
Verified email at eng.au.dk
Title
Cited by
Cited by
Year
Automated detection and recognition of wildlife using thermal cameras
P Christiansen, KA Steen, RN Jørgensen, H Karstoft
Sensors 14 (8), 13778-13793, 2014
1092014
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
742016
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
382016
Fieldsafe: dataset for obstacle detection in agriculture
MF Kragh, P Christiansen, MS Laursen, M Larsen, KA Steen, O Green, ...
Sensors 17 (11), 2579, 2017
232017
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
152018
Unsuperpoint: End-to-end unsupervised interest point detector and descriptor
PH Christiansen, MF Kragh, Y Brodskiy, H Karstoft
arXiv preprint arXiv:1907.04011, 2019
132019
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
92017
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
82015
Automated classification of seedlings using computer vision
M Dyrmann, P Christiansen
Aarhus University, School of Engineering, Technical Information Technology, 2014
8*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
72018
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
72016
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
42016
Towards inverse sensor mapping in agriculture
T Korthals, M Kragh, P Christiansen, U Rückert
arXiv preprint arXiv:1805.08595, 2018
32018
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
32015
Towards a DSL for Perception-Based Safety Systems
JTM Ingibergsson, SD Suvei, MK Hansen, P Christiansen, UP Schultz
arXiv preprint arXiv:1603.01965, 2016
2*2016
TractorEYE: Vision-based Real-time Detection for Autonomous Vehicles in Agriculture
P Christiansen
Department of Engineering, Aarhus University, 2017
12017
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
12016
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
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
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
2017
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Articles 1–20