Gebreyesus, G., Cheruiyot Bett , R., Nakimbugwe, D.
, Hansen, L. S., Nielsen, H. M., Karstoft, H., Bjerge, K., Nkirote Kunyanga , C., MBI Tanga, C., Mwikirize, C., Akol, R., Katumba, A., Khamis, F., Kinyua, J., Walusimbi, S., Geoffrey, S., Roos, N.
& Sahana, G. (2024).
Prospects of implementing black soldier fly (BSF) selective breeding in Kenya and Uganda: Status from the FlyGene Project. Abstract from Insects for the Green Economy: Sustainable Food
Systems and Livelihoods in Africa, Nairobi, Kenya.
https://qgg.au.dk/fileadmin/site_files/mb/QGG/Billeder/FLYgene/book-of-abstracts-insects-for-the-green-economy-conference-feb2024.pdf
Nawoya, S., Ssemakula, F., Akol, R.
, Geissmann, Q., Karstoft, H., Bjerge, K., Mwikirize, C., Katumba, A.
& Gebreyesus, G. (2024).
Computer vision and deep learning in insects for food and feed production: A review.
Computers and Electronics in Agriculture,
216, Article 108503.
https://doi.org/10.1016/j.compag.2023.108503
Nawoya, S., Geissmann, Q., Karstoft, H., Bjerge, K., Akol, R., Katumba, A., Mwikirize, C.
& Gebreyesus, G. (2024).
Computer-vision based prediction of body traits and larval sex in black soldier fly. Abstract from Insects for the Green Economy: Sustainable Food
Systems and Livelihoods in Africa, Nairobi, Kenya.
https://qgg.au.dk/fileadmin/site_files/mb/QGG/Billeder/FLYgene/book-of-abstracts-insects-for-the-green-economy-conference-feb2024.pdf
Sahana, G., Gebreyesus, G., Cheruiyot Bett , R., Kinyua, J., Roos, N., MBI Tanga, C., Mwikirize, C., Akol, R., Khamis, F. M.
, Karstoft, H., Bjerge, K., Nkirote Kunyanga , C.
, Hansen, L. S., Nielsen, H. M., Lund, M. S., Geoffrey, S., Walusimbi, S. & Nakimbugwe, D. (2024).
FLYgene: Advancing Sustainable Breeding Programs and Genomic Tools for Black Soldier Fly (Hermetia illucens) in Kenya and Uganda. In
Book of Abstracts of the 75th Annual Meeting of the European Federation of Animal Science (pp. 633-633)
https://docs.eaap.org/boa/2024_Florence_EAAP_Book_Abstracts.pdf
Bjerge, K., Geissmann, Q., Alison, J., Mann, H. M. R., Høye, T. T., Dyrmann, M. & Karstoft, H. (2023).
Hierarchical classification of insects with multitask learning and anomaly detection.
Ecological Informatics,
77, Article 102278.
https://doi.org/10.1016/j.ecoinf.2023.102278
Bjerge, K., Geissmann, Q., Alison, J., Mann, H. M. R., Høye, T. T., Dyrmann, M. & Karstoft, H. (2023).
Hierarchical Classification of Insects with Multitask Learning and Anomaly Detection. bioRxiv.
https://doi.org/10.1101/2023.06.29.546989
Dobbs, A. M., Ginn, D.
, Skovsen, S. K., Yadav, R., Jha, P., Bagavathiannan, M. V., Mirsky, S. B., Reberg-Horton, C. S. & Leon, R. G. (2023).
Using structure-from-motion to estimate cover crop biomass and characterize canopy structure.
Field Crops Research,
302, Article 109099.
https://doi.org/10.1016/j.fcr.2023.109099
Gislum, R., Larsen, R., Thomsen, I. K., Greve, M. B., Hansen, E. M. & Nyholm Jørgensen, R., (2023).
Betingelse for indsamling af data til brug for omregningsfaktor mellem NDV/NDRE og planteoptag af kvælstof, No. 2023-0543874, 8 p., Aug 23, 2023. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug
Skovsen, S. K., Kutugata, M., Jennewein, J., Reberg-Horton, C. S. & Mirsky, S. B. (2023).
Detailed Species Competition Mapping of Mixed Cover Crop Species Using Tractor Mounted Color Camera and Computer Vision. Abstract from 2023 ASA/CSSA/SSSA International Annual Meeting, St. Louis, Missouri, United States.
Dobbs, A. M., Ginn, D.
, Skovsen, S. K., Bagavathiannan, M. V., Mirsky, S. B., Reberg-Horton, C. S. & Leon, R. G. (2022).
New directions in weed management and research using 3D imaging.
Weed Science,
70(6), 641-647.
https://doi.org/10.1017/wsc.2022.56
Kragh, M. F., Rimestad, J., Lassen, J. T., Berntsen, J.
& Karstoft, H. (2022).
Predicting embryo viability based on self-supervised alignment of time-lapse videos.
IEEE Transactions on Medical Imaging,
41(2), 465-475.
https://doi.org/10.1109/TMI.2021.3116986
Farkhani, S., Skovsen, S. K., Dyrmann, M., Nyholm Jørgensen, R. & Karstoft, H. (2021).
Weed classification using explainable multi-resolution slot attention.
Sensors,
21(20), Article 6705.
https://doi.org/10.3390/s21206705
Lati, R. N.
, Rasmussen, J., Andujar, D., Dorado, J., Berge, T. W., Wellhausen, C., Pflanz, M., Nordmeyer, H., Schirrmann, M., Eizenberg, H., Neve, P.
, Jørgensen, R. N. & Christensen, S. (2021).
Site-specific weed management—constraints and opportunities for the weed research community: Insights from a workshop.
Weed Research,
61(3), 147-153.
https://doi.org/10.1111/wre.12469
Lindahl Petersen , K., Ladegaard Jensen, K., Back Nielsen, M., Pas, L.-C., Jensen, N.-P., Nielsen, P. R., Bøjer, O. M.
, Nyholm Jørgensen, R., Laursen, M. S., Teimouri, N. & Hartmann, B. (2021).
Analyse af mulige herbicidbesparelser ved brug af erfaringer og data fra RoboWeedMaPS. Datalogisk Institut.
https://datalogisk.dk/wp-content/uploads/2021/03/MST_20rapport_version_2_2002092021.pdf
Skovsen, S. K., Laursen, M. S., Kristensen, R. K., Rasmussen, J., Dyrmann, M., Eriksen, J., Gislum, R., Nyholm Jørgensen, R. & Karstoft, H. (2021).
Robust Species Distribution Mapping of Crop Mixtures Using Color Images and Convolutional Neural Networks.
Sensors,
21( 1), Article 175.
https://doi.org/10.3390/s21010175
Somerville, G. J., Mathiassen, S. K., Melander, B., Bøjer, O. M.
& Nyholm Jørgensen, R. (2021).
Analysing the number of images needed to create robust variable spray maps.
Precision Agriculture,
22(5), 1377-1396.
https://doi.org/10.1007/s11119-021-09800-3
Farkhani, S., Skovsen, S. K., Mortensen, A. K., Laursen, M. S., Nyholm Jørgensen, R. & Karstoft, H. (2020).
Initial evaluation of enriching satellite imagery using sparse proximal sensing in precision farming. In C. M. U. Neale & A. Maltese (Eds.),
Remote Sensing for Agriculture, Ecosystems, and Hydrology XXII (Vol. 11528). Article 115280A SPIE - International Society for Optical Engineering.
https://doi.org/10.1117/12.2573626
Madsen, S. L., Mathiassen, S. K., Dyrmann, M., Laursen, M. S., Paz, L.-C. & Nyholm Jørgensen, R. (2020).
Open Plant Phenotype Database of Common Weeds in Denmark.
Remote Sensing,
12(8), Article 1246.
https://doi.org/10.3390/rs12081246
Christiansen, M. P.
, Teimouri, N., Laursen, M. S., Mikkelsen, B. F.
, Jorgensen, R. N. & Sorensen, C. A. G. (2019).
Preprocessed sentinel-1 data via a web service focused on agricultural field monitoring.
IEEE Access,
7(1), 65139-65149. Article 8715769.
https://doi.org/10.1109/ACCESS.2019.2917063
Eriksen, J., Frandsen, T. S., Knudsen, L.
, Skovsen, S., Nyholm Jørgensen, R., Steen, K. A.
, Green, O. & Rasmussen, J. (2019).
Nitrogen fertilization of grass-clover leys. In O. Huguenin-Elie, B. Studer, R. Kölliker, D. Reheul, M. Probo, P. Barre, U. Feuerstein, I. Roldan-Ruiz, P. Mariotte & A. Hopkins (Eds.),
Improving sown grasslands through breeding and management: Proceedings of the Joint 20th Symposium of the European Grassland Federation and the 33rd Meeting of the EUCARPIA Section "Fodder Crops and Amenity Grasses", Zürich, Switzerland, 24-27 June 2019 (pp. 103-109). Wageningen Academic Publishers.
Farkhani, S., Kragh, M. F., Christiansen, P. H., Nyholm Jørgensen, R. & Karstoft, H. (2019).
Sparse-to-Dense Depth Completion in Precision Farming. In
Proceedings of the 3rd International Conference on Vision, Image and Signal Processing, ICVISP 2019: Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Article 35 Association for Computing Machinery.
https://doi.org/10.1145/3387168.3387230
Gislum, R., Nyholm Jørgensen, R., Thomsen, I. K., Hansen, E. M. & Olesen, J. E., (2019).
Beskrivelse af setup for vidensindsamling og måling af NDVI-værdi i pilotprojekt om biomasse, No. 2019-760-001283, 3 p., Jul 03, 2019.