Mads Dyrmann
Mads Dyrmann
Associate Professor, Aarhus University; Honoary Research Associalte, University of Oxford
Verified email at - Homepage
Cited by
Cited by
Plant species classification using deep convolutional neural network
M Dyrmann, H Karstoft, HS Midtiby
Biosystems engineering 151, 72-80, 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
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
Semantic segmentation of mixed crops using deep convolutional neural network.
AK Mortensen, M Dyrmann, H Karstoft, RN Jørgensen, R Gislum
Weed growth stage estimator using deep convolutional neural networks
N Teimouri, M Dyrmann, PR Nielsen, SK Mathiassen, GJ Somerville, ...
Sensors 18 (5), 1580, 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
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
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
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
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
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
Generating artificial images of plant seedlings using generative adversarial networks
SL Madsen, M Dyrmann, RN Jørgensen, H Karstoft
Biosystems Engineering 187, 147-159, 2019
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
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
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
Automatic Detection and Classification of Weed Seedlings under Natural Light Conditions
M Dyrmann
University of Southern Denmark, 2017
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
Automated Classification of Seedlings Using Computer Vision: Pattern Recognition of Seedlings Combining Features of Plants and Leaves for Improved Discrimination
M Dyrmann, P Christiansen
Aarhus University, 2014
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
Accurate image-based identification of macroinvertebrate specimens using deep learning—How much training data is needed?
TT Høye, M Dyrmann, C Kjær, J Nielsen, M Bruus, CL Mielec, ...
PeerJ 10, e13837, 2022
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