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Mikkel Fly Kragh
Mikkel Fly Kragh
Senior Research Scientist, Vitrolife
Verified email at vitrolife.com
Title
Cited by
Cited by
Year
Kinect depth sensor evaluation for computer vision applications
MR Andersen, T Jensen, P Lisouski, AK Mortensen, MK Hansen, ...
Aarhus University, 1-37, 2012
2922012
Object detection and terrain classification in agricultural fields using 3D lidar data
M Kragh, RN Jørgensen, H Pedersen
International conference on computer vision systems, 188-197, 2015
562015
Automatic behaviour analysis system for honeybees using computer vision
GJ Tu, MK Hansen, P Kryger, P Ahrendt
Computers and Electronics in Agriculture 122, 10-18, 2016
542016
Automatic grading of human blastocysts from time-lapse imaging
MF Kragh, J Rimestad, J Berntsen, H Karstoft
Computers in biology and medicine 115, 103494, 2019
522019
FieldSAFE: Dataset for Obstacle Detection in Agriculture
MF Kragh, P Christiansen, MS Laursen, M Larsen, KA Steen, O Green, ...
Sensors 17 (11), 2017
492017
Unsuperpoint: End-to-end unsupervised interest point detector and descriptor
PH Christiansen, MF Kragh, Y Brodskiy, H Karstoft
arXiv preprint arXiv:1907.04011, 2019
472019
Multimodal obstacle detection in unstructured environments with conditional random fields
M Kragh, J Underwood
Journal of Field Robotics 37 (1), 53-72, 2020
222020
Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences
J Berntsen, J Rimestad, JT Lassen, D Tran, MF Kragh
Plos one 17 (2), e0262661, 2022
152022
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
132018
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
132017
Embryo selection with artificial intelligence: how to evaluate and compare methods?
MF Kragh, H Karstoft
Journal of Assisted Reproduction and Genetics 38 (7), 1675-1689, 2021
112021
Advanced sensor platform for human detection and protection in autonomous farming
P Christiansen, M Kragh, KA Steen, H Karstoft, RN Jørgensen
European Conference on Precision Agriculture 10, 291-298, 2015
92015
Multimodal obstacle detection and evaluation of occupancy grid mapping in agriculture.
M Kragh, P Christiansen, T Korthals, T Jungeblut, H Karstoft, ...
CIGR-AgEng Conference, 26-29 June 2016, Aarhus, Denmark. Abstracts and Full …, 2016
82016
Towards inverse sensor mapping in agriculture
T Korthals, M Kragh, P Christiansen, U Rückert
arXiv preprint arXiv:1805.08595, 2018
52018
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
32019
Lidar-Based Obstacle Detection and Recognition for Autonomous Agricultural Vehicles
MF Kragh
AU Library Scholarly Publishing Services: Aarhus, Denmark, 2018
32018
3D impurity inspection of cylindrical transparent containers
M Kragh, K Bjerge, P Ahrendt
Measurement Science and Technology 28 (1), 017002, 2016
22016
Predicting embryo viability based on self-supervised alignment of time-lapse videos
MF Kragh, J Rimestad, JT Lassen, J Berntsen, H Karstoft
IEEE Transactions on Medical Imaging 41 (2), 465-475, 2021
12021
O-123 Calibration of artificial intelligence (AI) models is necessary to reflect actual implantation probabilities with image-based embryo selection
MF Kragh, JT Lassen, J Rimestad, J Berntsen
Human Reproduction 36 (Supplement_1), deab126. 048, 2021
12021
Towards a DSL for perception-based safety systems
JTM Ingibergsson, SD Suvei, MK Hansen, P Christiansen, UP Schultz
arXiv preprint arXiv:1603.01965, 2016
12016
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