| Site‐specific weed control technologies S Christensen, HT Søgaard, P Kudsk, M Nørremark, I Lund, ES Nadimi, ... Weed Research 49 (3), 233-241, 2009 | 316 | 2009 |
| Designing and testing a UAV mapping system for agricultural field surveying MP Christiansen, MS Laursen, RN Jørgensen, S Skovsen, R Gislum Sensors 17 (12), 2703, 2017 | 208 | 2017 |
| Monitoring and classifying animal behavior using ZigBee-based mobile ad hoc wireless sensor networks and artificial neural networks ES Nadimi, RN Jørgensen, V Blanes-Vidal, S Christensen Computers and electronics in agriculture 82, 44-54, 2012 | 188 | 2012 |
| Automated detection and recognition of wildlife using thermal cameras P Christiansen, KA Steen, RN Jørgensen, H Karstoft Sensors 14 (8), 13778-13793, 2014 | 185 | 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 | 173 | 2016 |
| RoboWeedSupport-Detection of weed locations in leaf occluded cereal crops using a fully convolutional neural network M Dyrmann, RN Jørgensen, HS Midtiby Advances in Animal Biosciences 8 (2), 842-847, 2017 | 163 | 2017 |
| A public image database for benchmark of plant seedling classification algorithms TM Giselsson, RN Jørgensen, PK Jensen, M Dyrmann, HS Midtiby arXiv preprint arXiv:1711.05458, 2017 | 147 | 2017 |
| Semantic segmentation of mixed crops using deep convolutional neural network. AK Mortensen, M Dyrmann, H Karstoft, RN Jørgensen, R Gislum | 117 | 2016 |
| Monitoring and modeling temperature variations inside silage stacks using novel wireless sensor networks O Green, ES Nadimi, V Blanes-Vidal, RN Jørgensen, IMLD Storm, ... Computers and Electronics in Agriculture 69 (2), 149-157, 2009 | 115 | 2009 |
| Estimation of leaf area index in cereal crops using red–green images K Kirk, HJ Andersen, AG Thomsen, JR Jørgensen, RN Jørgensen Biosystems Engineering 104 (3), 308-317, 2009 | 110 | 2009 |
| Weed growth stage estimator using deep convolutional neural networks N Teimouri, M Dyrmann, PR Nielsen, SK Mathiassen, GJ Somerville, ... Sensors 18 (5), 1580, 2018 | 102 | 2018 |
| 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 | 88 | 2016 |
| A novel spatio-temporal FCN-LSTM network for recognizing various crop types using multi-temporal radar images N Teimouri, M Dyrmann, RN Jørgensen Remote Sensing 11 (8), 990, 2019 | 78 | 2019 |
| Pixel-wise classification of weeds and crops in images by using a fully convolutional neural network M Dyrmann, AK Mortensen, HS Midtiby, RN Jørgensen Proceedings of the International Conference on Agricultural Engineering …, 2016 | 74 | 2016 |
| 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 | 74 | 2015 |
| Fieldsafe: dataset for obstacle detection in agriculture MF Kragh, P Christiansen, MS Laursen, M Larsen, KA Steen, O Green, ... Sensors 17 (11), 2579, 2017 | 70 | 2017 |
| N2O emission from energy crop fields of Miscanthus “Giganteus” and winter rye RN Jørgensen, BJ Jørgensen, NE Nielsen, M Maag, AM Lind Atmospheric Environment 31 (18), 2899-2904, 1997 | 69 | 1997 |
| Towards an open software platform for field robots in precision agriculture K Jensen, M Larsen, SH Nielsen, LB Larsen, KS Olsen, RN Jørgensen Robotics 3 (2), 207-234, 2014 | 67 | 2014 |
| Modelling nitrogen and phosphorus content at early growth stages in spring barley using hyperspectral line scanning LK Christensen, BS Bennedsen, RN Jørgensen, H Nielsen Biosystems Engineering 88 (1), 19-24, 2004 | 62 | 2004 |
| N2O emission immediately after rainfall in a dry stubble field RN JØrgensen, BJ JØrgensen, NE Nielsen Soil Biology and Biochemistry 30 (4), 545-546, 1998 | 58 | 1998 |
Claus Aage Grøn SørensenProfessor, Operations Management在 eng.au.dk 的电子邮件经过验证
