Plant species classification using deep convolutional neural network M Dyrmann, H Karstoft, HS Midtiby Biosystems engineering 151, 72-80, 2016 | 690 | 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 | 169 | 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 | 167 | 2017 |
Semantic segmentation of mixed crops using deep convolutional neural network. AK Mortensen, M Dyrmann, H Karstoft, RN Jørgensen, R Gislum | 119 | 2016 |
Weed growth stage estimator using deep convolutional neural networks N Teimouri, M Dyrmann, PR Nielsen, SK Mathiassen, GJ Somerville, ... Sensors 18 (5), 1580, 2018 | 110 | 2018 |
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 | 86 | 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 | 75 | 2016 |
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 |
Open plant phenotype database of common weeds in Denmark S Leminen Madsen, SK Mathiassen, M Dyrmann, MS Laursen, LC Paz, ... Remote Sensing 12 (8), 1246, 2020 | 60 | 2020 |
Accurate detection and identification of insects from camera trap images with deep learning K Bjerge, J Alison, M Dyrmann, CE Frigaard, HMR Mann, TT Høye PLOS Sustainability and Transformation 2 (3), e0000051, 2023 | 56 | 2023 |
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 |
Generating artificial images of plant seedlings using generative adversarial networks SL Madsen, M Dyrmann, RN Jørgensen, H Karstoft Biosystems Engineering 187, 147-159, 2019 | 35 | 2019 |
Using a fully convolutional neural network for detecting locations of weeds in images from cereal fields M Dyrmann, S Skovsen, MS Laursen, RN Jørgensen The 14th International Conference on Precision Agriculture, 1-7, 2018 | 27 | 2018 |
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 | 27 | 2018 |
Hierarchical classification of insects with multitask learning and anomaly detection K Bjerge, Q Geissmann, J Alison, HMR Mann, TT Høye, M Dyrmann, ... Ecological Informatics 77, 102278, 2023 | 25 | 2023 |
RoboWeedSupport-Sub millimeter weed image acquisition in cereal crops with speeds up till 50 km/h MS Laursen, RN Jørgensen, M Dyrmann, R Poulsen International Journal of Agricultural and Biosystems Engineering 11 (4), 317-321, 2017 | 24 | 2017 |
Automatic Detection and Classification of Weed Seedlings under Natural Light Conditions M Dyrmann University of Southern Denmark, 2017 | 18 | 2017 |
Camera assisted roadside monitoring for invasive alien plant species using deep learning M Dyrmann, AK Mortensen, L Linneberg, TT Høye, K Bjerge Sensors 21 (18), 6126, 2021 | 16 | 2021 |
Robust species distribution mapping of crop mixtures using color images and convolutional neural networks SK Skovsen, MS Laursen, RK Kristensen, J Rasmussen, M Dyrmann, ... Sensors 21 (1), 175, 2020 | 15 | 2020 |
Predicting dry matter composition of grass clover leys using data simulation and camera-based segmentation of field canopies into white clover, red clover, grass and weeds S Skovsen, M Dyrmann, J Eriksen, R Gislum, H Karstoft, RN Jørgensen Proceedings of the 14th International Conference on Precision Engineering, 5079, 2018 | 14 | 2018 |