Publications by Signal Processing & Machine Learning

Are you looking for publications by Section of Signal Processing & Machine Learning? On this page you can find all the publications made by the Section of Signal Processing & Machine Learning - Department of Electrical and Computer Engineering, Aarhus University.

Below you can find a list of all the publications, their publishing date, their author(s), and titles. The list can be sorted by date, author, and title:

List of Publications

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Steen, K. A., Therkildsen, O. R., Karstoft, H. & Green, O. (2012). A Vocal-Based Analytical Method for Goose Behaviour Recognition. Sensors, 12, 3773-3788. https://doi.org/10.3390/s120303773

Steen, K. A., Therkildsen, O. R., Karstoft, H. & Green, O. (2012). Wildlife Communication: Electrical and Computer Engineering. Aarhus University, Department of Engineering. Technical report Nr. ECE-TR-7 https://pure.au.dk/portal/files/45572923/samlet_TCR_7_ver2.pdf

Steen, K. A., Therkildsen, O. R., Karstoft, H. & Green, O. (2012). Video-Based Detection of Goose Behaviours. Afhandling præsenteret på Agriculture & Engineering for a Healthier Life, Valencia, Spanien. http://cigr.ageng2012.org/images/fotosg/tabla_137_C0358.pdf

Steen, K. A., Villa-Henriksen, A., Therkildsen, O. R., Karstoft, H. & Green, O. (2012). Automatic Detection of Animals using Thermal Imaging. Afhandling præsenteret på Agriculture & Engineering for a Healthier Life, Valencia, Spanien. http://cigr.ageng2012.org/images/fotosg/tabla_137_C0392.pdf

Steen, K. A., Therkildsen, O. R., Karstoft, H. & Green, O. (2013). An Audio Based Adaptive Goose Scaring Device. Afhandling præsenteret på CIOSTA XXXV Conference, Billund, Danmark.

Steen, K. A., Therkildsen, O. R., Green, O. & Karstoft, H. (2013). Audio-Visual Recognition of Goose Flocking Behavior. International Journal of Pattern Recognition and Artificial Intelligence, 27(7). https://doi.org/10.1142/S0218001413500201

Steen, K. A., Therkildsen, O. R., Karstoft, H. & Green, O. (2014). Audio-Based Detection and Recognition of Conflict Species in Outdoor Environments Using Pattern Recognition Methods. Applied Engineering in Agriculture, 30(1), 89-96. https://doi.org/10.13031/aea.30.9817

Steen, K. A., McClellan, J. H., Green, O. & Karstoft, H. (2014). Acoustic Source Tracking in Long Baseline Microphone Arrays. Applied Acoustics, 87, 38–45. https://doi.org/10.1016/j.apacoust.2014.06.002

Steen, K. A. & Karstoft, H. (2014). The acoustic adaptive frightening device-framework and algorithms. I 2014 IEEE Global Conference on Signal and Information Processing : GlobalSIP 2014 (s. 1117-1121). IEEE. https://doi.org/10.1109/GlobalSIP.2014.7032295

Steen, K. A., Therkildsen, O. R., Green , O. & Karstoft, H. (2015). Detection of Bird Nests during Mechanical Weeding by Incremental Background Modeling and Visual Saliency. Sensors, 15(3), 5096-5111. https://doi.org/10.3390/s150305096

Steen, K. A., Therkildsen, O. R., Karstoft, H. & Green, O. (2015). An adaptive scaring device. International Journal of Sustainable Agricultural Management and Informatics, 1(2), 130-141. https://doi.org/10.1504/IJSAMI.2015.070746

Steen, K. A., Christiansen, P., Karstoft, H. & Nyholm Jørgensen, R. (2016). Using Deep Learning to Challenge Safety Standard for Highly Autonomous Machines in Agriculture. Journal of Imaging, 2(1), Artikel 6. https://doi.org/10.3390/jimaging2010006

Steen, K. A., Grooters, K., Høilund, C., Rasmussen, J., Nyholm Jørgensen, R., Dyrmann, M. & Green, O. (2018). Automated Weed Intensity Mapping. I G. K. P.W.G. , C. Lokhorst, A. H. Ipema, C. Kempenaar, C. M. Groenestein , C. G. van Oostrum & N. J. Ros (red.), Book of Abstracts of the European Conference on Agricultural Engineering: AgEng2018 (s. 109). Wageningen University. https://doi.org/10.18174/471678

Steen, K. A., Delebasse, S., Grooters, K., Høilund, C., Dyrmann, M., Skovsen, S., Nyholm Jørgensen, R. & Green, O. (2018). In-field Potato Diseases Detection. I P. W. G. Groot Koerkamp, C. Lokhorst, A. H. Ipema, C. Kempenaar, C. M. Groenestein, C. G. van Oostrum & N. J. Ros (red.), Book of Abstracts of the European Conference on Agricultural Engineering: AgEng2018 (s. 111). Wageningen University. https://doi.org/10.18174/471678

Ssemakula, F., Nawoya, S., Kunyanga, C. N., Akol, R., Nakimbugwe, D., Bett, R. C., Karstoft, H., Bjerge, K., Katumba, A., Mwikirize, C. & Gebreyesus, G. (2025). Emerging technologies for fast determination of nutritional quality and safety of insects for food and feed: A review. Computers and Electronics in Agriculture, 239, Artikel 111126. https://doi.org/10.1016/j.compag.2025.111126

Sridharan, K. S., Johnsen, E. L., Nielsen, A. H., Beniczky, S., Johansen, L. G., Sunde, N. & Østergaard, K. (2015). Effect of deep brain stimulation (DBS) and medication on somatosensory function in Parkinson’s disease (PD). Poster-session præsenteret på Nordic Congress of Clinical Neurophysiology, Helsingør, Danmark.

Sridharan, K. S., Johnsen, E. L., Beniczky, S., Johansen, L. G., Sunde, N. & Østergaard, K. (2015). Studying somatosensory function in Parkinson’s disease using Magnetoencephalography. Poster-session præsenteret på PhD day 2015, Aarhus University, Danmark.

Sridharan, K. S., Højlund, A., Sunde, N., Johnsen, E. L., Johansen, L. G., Beniczky, S. & Østergaard, K. (2016). How do treatments affect somatosensory processing in Parkinson's disease - A MEG study. Poster-session præsenteret på PhD Day 2016, Aarhus, Danmark.

Sridharan, K. S., Højlund, A., Johnsen, E. L., Sunde, N., Johansen, L. G., Beniczky, S. & Østergaard, K. (2017). Differentiated effects of deep brain stimulation and medication on somatosensory processing in Parkinson's disease. Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 128(7), 1327-1336. https://doi.org/10.1016/j.clinph.2017.04.014

Spahr, A., Bozorgtabar, B. & Thiran, J.-P. (2021). Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-rays.

Sørensen, C. A. G., Bak, T. & Jørgensen, R. (2004). Mission planner for agricultural robotics. I AgEng 2004, Leuven, Belgium. Book of Abstracts, ISBN 90-76019-258, 894-895. Paper on CD, 8 pp. (s. 8) https://www.researchgate.net/publication/280315702_Mission_planner_for_agricultural_robotics

Sørensen, C. A. G., Jørgensen, R., Jensen, L. A. & Madsen, S. B. (2005). Fleet support system. I Proc. XXXI CIOSTA-CIGR V cong. on Increasing Work Efficiency in Agriculture, Horticulture and Forestry, University of Hohenheim, Stuttgart, Germany. ISB https://www.researchgate.net/publication/280306216_Fleet_support_system

Sørensen, C. G., Jørgensen, R. N., Pedersen, J. M. & Nørremark, M. (2006). HortiBot: Application of Quality Function Deployment (QFD) Method for Horticultural Robotic Tool Carrier Design Planning - Part II: Paper No. 067021. I Proc. ASABE Annual Meeting http://asae.frymulti.com/request.asp?JID=5&AID=21015&CID=por2006&T=1

Sørensen, C. A. G., Nørremark, M., Jørgensen, R., Jensen, K., Jensen, L. A. & Maagaard, J. (2007). Hortibot: Feasibility study of a plant nursing robot performing weeding operations - part IV: Paper No. 077019. I Ikke angivet ASABE - American Society of Agricultural and Biological Engineers. http://asae.frymulti.com/techpapers.asp?confid=min2007

Sørensen, C. A. G., Green, O., Nørremark, M., Jørgensen, R., Jensen, K., Maagaard, J. & Jensen, L. A. (2007). Feasibility study of a plant nursing robot performing weeding operations. Abstract fra NJF seminar: Modellling in Agriculture, Jelgava, Letland.

Sørensen, L. T., Schultz, N., Christensen, D. S., Jiang, B., Dalsgaard, P., Jensen, J. J., Larsen, L. B. & Pedersen, C. F. (2004). A user centred methodology for establishing PAN/PN scenarios. Afhandling præsenteret på My Personal Adaptive Global NET: Visions and beyond, Shanghai, Kina.

Sørensen, C. A. G., Green, O., Nørremark, M., Jørgensen, R. N., Jensen, K., Maagaard, J. & Jensen, L. A. (2009). Feasibility study of a plant nursing robot performing weeding operations. I Proceedings of the NJF Seminar Nordic Association of Agricultural Scientists.

Sørensen, L., Saugstrup, D., Schultz, N., Larsen, J., Jensen, K. L., Larsen, L. B., Pedersen, C. F., Kaldanis, V. & Vila, J. (2005). User centric scenarios for PNs of a valid architecture. Information Society Technologies, My Personal Adaptive Global NET (MAGNET), IST 507102.

Sørensen, R. A., Rasmussen, J., Nielsen, J. & Nyholm Jørgensen, R. (2017). Thistle detection using convolutional neural networks: EFITA 2017 Presentation. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=_G_xLchBOl4

Sørensen, R. A., Skovsen, S., Christiansen, P. & Karstoft, H. (2017). Embedded Visual Perception for Autonomous Agricultural Machines Using Lightweight Convolutional Neural Networks. International Journal of Agricultural and Biosystems Engineering, 11(4), 1296. Artikel 63060. https://www.waset.org/abstracts/63060

Sørensen, R. A., Rasmussen, J., Nielsen, J. & Nyholm Jørgensen, R. (2017). Thistle detection using convolutional neural networks. I 2017 EFITA WCCA Congress - European conference dedicated to the future use of ICT: Conference Proceedings (s. 161-162). Institut National de Recherche en Sciences et Technologies pour l'Environnement et l'Agriculture. http://www.efita2017.org/wp-content/uploads/2017/09/EFITA_WCCA_2017_proceedings.pdf#page=187

Sørensen, R. A., Nielsen, M. & Karstoft, H. (2019). Deep Reinforcement Learning for Route Optimization in Baggage Handling Systems. I S. Y. Yurish (red.), Advances in Signal Processing and Artificial Intelligence: Proceedings of the 1st International Conference on Advances in Signal Processing and Artifical Intelligence (s. 29-33). Artikel 11 IFSA Publishing.

Sørensen, R. A., Nielsen, M. & Karstoft, H. (2020). Routing in congested baggage handling systems using deep reinforcement learning. Integrated Computer-Aided Engineering, 27(2), 139-152. https://doi.org/10.3233/ICA-190613

Sørensen, R. A., Rosenberg, J. & Karstoft, H. (2021). Baggage Routing with Scheduled Departures using Deep Reinforcement Learning. I Proceedings - 2021 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2021 (s. 13-19). IEEE. https://doi.org/10.1109/ISCSIC54682.2021.00014

Somerville, G. J., Nyholm Jørgensen, R., Bojer, O. M., Rydahl, P., Dyrmann, M., Andersen, P., Jensen, N.-P. & Green, O. (2019). Marrying futuristic weed mapping with current herbicide sprayer capacities. I J. V. Stafford (red.), Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019 (s. 231-237). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-888-9_28

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

So, P., Sarabakha, A., Wu, F., Culha, U., Abu-Dakka, F. & Haddadin, S. (2024). Digital Robot Judge: Building a Task-centric Performance Database of Real-World Manipulation With Electronic Task Boards. IEEE Robotics and Automation Magazine, 31(4), 32-44. https://doi.org/10.1109/MRA.2023.3336473

S. Nadimi, E., Jørgensen, R. N. & Oudshoorn, F. W. (2011). Method and system for estimating herbage uptake of an animal. (Patentnummer PCT/DK2010/050334).

S. Nadimi, E., Blanes-Vidal, V. & Jørgensen, R. N. (2010). OPTIMIZATION OF ENERGY CONSUMPTION DURING GRAIN DRYING process using wireless sensor networks.

S. Nadimi, E., Jørgensen, R. N., Blanes-Vidal, V. & Christensen, S. (2012). Monitoring and classifying animal behavior using ZigBee-based mobile ad hoc wireless sensor networks and artificial neural networks. Computers and Electronics in Agriculture, 82, 44-54. https://doi.org/10.1016/j.compag.2011.12.008

S. Nadimi, E., Blanes-Vidal, V., Jørgensen, R. N. & Christensen, S. (2011). Energy generation for an ad hoc wireless sensor network-based monitoring system using animal head movement. Computers and Electronics in Agriculture, 75(2), 238-242. https://doi.org/10.1016/j.compag.2010.11.008

S. Nadimi, E., Blanes-Vidal, V. & Jørgensen, R. N. (2009). ENERGY GENERATION FOR WIRELESS SENSOR NETWORK BASED animal behavior monitoring system.

Skovsen, S., Dyrmann, M., Mortensen, A. K., Steen, K. A., Green, O., Eriksen, J., Gislum, R., Nyholm Jørgensen, R. & Karstoft, H. (2017). Estimation of the Botanical Composition of Clover-Grass Leys from RGB Images Using Data Simulation and Fully Convolutional Neural Networks. Sensors, 17(12), Artikel 2930. https://doi.org/10.3390/s17122930

Skovsen, S., Laursen, M. S., Nyholm Jørgensen, R. & Karstoft, H. (2018). Mapping of Clover Grass Leys using Image Recognition. Poster-session præsenteret på DTU and DIKU Summer School: Optimization in Image Analysis, Danmark. http://optimization-image-analysis.compute.dtu.dk/posters/soren_skovsen.pdf

Skovsen, S., Dyrmann, M., Eriksen, J., Gislum, R., Karstoft, H. & Nyholm Jørgensen, R. (2018). 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. I Proceedings of the 14th International Conference on Precision Engineering Artikel 5079 International Society of Precision Agriculture. https://ispag.org/proceedings/?action=abstract&id=5079

Skovsen, S., Dyrmann, M., Eriksen, J., Gislum, R., Karstoft, H. & Nyholm Jørgensen, R. (2018). 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. Abstract fra International Conference on Precision Agriculture, Montréal, Quebec, Canada. https://ispag.org/proceedings/?action=abstract&id=5079&search=authors

Skovsen, S., Dyrmann, M., Mortensen, A. K., Laursen, M. S., Gislum, R., Eriksen, J., Farkhani, S., Karstoft, H. & Nyholm Jørgensen, R. (2019). The GrassClover Image Dataset for Semantic and Hierarchical Species Understanding in Agriculture. Datasæt https://vision.eng.au.dk/grass-clover-dataset/

Skovsen, S., Dyrmann, M., Mortensen, A. K., Laursen, M. S., Gislum, R., Eriksen, J., Farkhani, S., Karstoft, H. & Nyholm Jørgensen, R. (2019). The GrassClover Image Dataset for Semantic and Hierarchical Species Understanding in Agriculture. Poster-session præsenteret på IEEE Conference on Computer Vision and Pattern Recognition 2019, Long Beach, California, USA.

Skovsen, S., Laursen, M. S., Gislum, R., Eriksen, J., Dyrmann, M., Mortensen, A. K., Farkhani, S., Karstoft, H., Jensen, N.-P. & Nyholm Jørgensen, R. (2019). Species distribution mapping of grass clover leys using images for targeted nitrogen fertilization. I J. V. Stafford (red.), Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019 (s. 639-645). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-888-9_79

Skovsen, S. K., Haraldsson, H., Davis, A., Karstoft, H. & Belongie, S. (2020). Decoupled Localization and Sensing with HMD-based AR for Interactive Scene Acquisition. I 2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) (s. 167-171). Artikel 9288396 IEEE. https://doi.org/10.1109/ISMAR-Adjunct51615.2020.00053

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Revideret 13.11.2025

AU Engineering