| Plant species classification using deep convolutional neural network M Dyrmann, H Karstoft, HS Midtiby Biosystems engineering 151, 72-80, 2016 | 685 | 2016 |
| Automated detection and recognition of wildlife using thermal cameras P Christiansen, KA Steen, RN Jørgensen, H Karstoft Sensors 14 (8), 13778-13793, 2014 | 196 | 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 | 184 | 2016 |
| Development of a real-time computer vision system for tracking loose-housed pigs P Ahrendt, T Gregersen, H Karstoft Computers and Electronics in Agriculture 76 (2), 169-174, 2011 | 181 | 2011 |
| Comparison of 10 perfusion MRI parameters in 97 sub-6-hour stroke patients using voxel-based receiver operating characteristics analysis S Christensen, K Mouridsen, O Wu, N Hjort, H Karstoft, G Thomalla, ... Stroke 40 (6), 2055-2061, 2009 | 157 | 2009 |
| Semantic segmentation of mixed crops using deep convolutional neural network. AK Mortensen, M Dyrmann, H Karstoft, RN Jørgensen, R Gislum | 119 | 2016 |
| 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 | 118 | 2019 |
| Unsuperpoint: End-to-end unsupervised interest point detector and descriptor PH Christiansen, MF Kragh, Y Brodskiy, H Karstoft arXiv preprint arXiv:1907.04011, 2019 | 100 | 2019 |
| 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 | 92 | 2016 |
| 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 | 90 | 2021 |
| Automatic Detection of Animals using Thermal Imaging KA Steen, A Villa-Henriksen, OR Therkildsen, H Karstoft, O Green Agriculture & Engineering for a Healthier Life, 2012 | 77* | 2012 |
| Fieldsafe: dataset for obstacle detection in agriculture MF Kragh, P Christiansen, MS Laursen, M Larsen, KA Steen, O Green, ... Sensors 17 (11), 2579, 2017 | 76 | 2017 |
| Segmentation of lettuce in coloured 3D point clouds for fresh weight estimation AK Mortensen, A Bender, B Whelan, MM Barbour, S Sukkarieh, H Karstoft, ... Computers and Electronics in Agriculture 154, 373-381, 2018 | 67 | 2018 |
| The GrassClover image dataset for semantic and hierarchical species understanding in agriculture S Skovsen, M Dyrmann, AK Mortensen, MS Laursen, R Gislum, J Eriksen, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 64 | 2019 |
| Estimation of the botanical composition of clover-grass leys from RGB images using data simulation and fully convolutional neural networks S Skovsen, M Dyrmann, AK Mortensen, KA Steen, O Green, J Eriksen, ... Sensors 17 (12), 2930, 2017 | 55 | 2017 |
| On-line separation and sorting of chicken portions using a robust vision-based intelligent modelling approach N Teimouri, M Omid, K Mollazade, H Mousazadeh, R Alimardani, ... Biosystems engineering 167, 8-20, 2018 | 51 | 2018 |
| IrradianceNet: Spatiotemporal deep learning model for satellite-derived solar irradiance short-term forecasting AH Nielsen, A Iosifidis, H Karstoft Solar Energy 228, 659-669, 2021 | 49 | 2021 |
| Generating artificial images of plant seedlings using generative adversarial networks SL Madsen, M Dyrmann, RN Jørgensen, H Karstoft Biosystems Engineering 187, 147-159, 2019 | 34 | 2019 |
| Routing in congested baggage handling systems using deep reinforcement learning RA Sørensen, M Nielsen, H Karstoft Integrated Computer-Aided Engineering 27 (2), 139-152, 2020 | 32 | 2020 |
| A vocal-based analytical method for goose behaviour recognition KA Steen, OR Therkildsen, H Karstoft, O Green Sensors 12 (3), 3773-3788, 2012 | 30 | 2012 |
