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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Midtiby, H. S., Åstrand, B., Jørgensen, O. & Jørgensen, R. N. (2016). Upper limit for context-based crop classification in robotic weeding applications. Biosystems Engineering, 146, 183-192. https://doi.org/10.1016/j.biosystemseng.2016.01.012

Christiansen, P. H., Kragh, M. F., Brodskiy, Y. & Karstoft, H. (2019). UnsuperPoint: End-to-end Unsupervised Interest Point Detector and Descriptor. arXiv.org. https://arxiv.org/abs/1907.04011

Govdeli, Y., Moheed Bin Muzaffar, S., Raj, R., Elhadidi, B. & Kayacan, E. (2019). Unsteady aerodynamic modeling and control of pusher and tilt-rotor quadplane configurations. Aerospace Science and Technology, 94, Article 105421. Advance online publication. https://doi.org/10.1016/j.ast.2019.105421

Jørgensen, J. R. & Jørgensen, R. N. (2007). Uniformity of wheat yield and quality using sensor assisted application of nitrogen. Precision Agriculture, 8(1-2), 63-73. https://doi.org/10.1007/s11119-006-9029-2

Oleksiienko, I. (2023). Uncertainty Estimation for 3D Object Detection and Tracking. Aarhus University.

D. Bedford, M., Gibson, D., Coggan, J., Siever, K., Wrana, A., Sobczak, D. & Alvarez Tunon, O. (2019). Ultrasonic Inspection of Flooded Mineshafts for Stability Monitoring. Mining Technology: Transactions of the Institutions of Mining and Metallurgy, 128(3), 177-185. https://doi.org/10.1080/25726668.2019.1607459

Green, O., Edwards, G. T. C., Jæger, C. D., Steen, K. A., Christiansen, P., Dyrmann, M. & Nyholm Jørgensen, R. (2016). Udviklingen inden for præcisionsjordbrug og tilknyttet udstyr. In Plantekongres 2016 (pp. 250-251). Article 66 https://www.landbrugsinfo.dk/Planteavl/Plantekongres/Filer/pl_plk2016_res_66_2_Ole_Green.pdf

Green, O., Nørremark, M., Lund, I. & Jørgensen, R. (2007). Udvikling af redskaber til HortiBot. Poster session presented at Temadag på Institut for Jordbrugsteknik - et vindue til fremtidens markteknologi, Horsens.

Hansen, J. G., Heiß, M., Kozłowski, M. & Kayacan, E. (2022). UAV Trajectory Evaluation in Large Industrial Environments: A Cost-Effective Solution. In 2022 European Control Conference (ECC) (pp. 1336-1341). IEEE. https://doi.org/10.23919/ECC55457.2022.9838352

Christiansen, M. P., Nyholm Jørgensen, R., Laursen, M. S. & Gislum, R. (2017). UAV LIDAR biomass estimation/Using Sentinel-1 to estimate yield potential. Poster session presented at DIGIT, Aarhus, Denmark.

Bozcan, I. & Kayacan, E. (2020). UAV-AdNet: Unsupervised Anomaly Detection using Deep Neural Networks for Aerial Surveillance. In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 1158-1164). Article 9341790 IEEE. https://doi.org/10.1109/IROS45743.2020.9341790

Kayacan, E. & Maslim, R. (2016). Type-2 Fuzzy Logic Trajectory Tracking Control of Quadrotor VTOL Aircraft With Elliptic Membership Functions. IEEE - ASME Transactions on Mechatronics, 22(1), 339-348. https://doi.org/10.1109/TMECH.2016.2614672

Sarabakha, A. (Producer), Fu, C. (Producer), Kayacan, E. (Producer) & Kumbasar, T. (Producer). (2016). Type-2 Fuzzy Logic Controllers Made Even Simpler: From Design to Deployment in Real-Time for Quadcopter UAVs. Pictures, Video and sound recordings (digital), YouTube. https://www.youtube.com/watch?v=Hz3f8N-30dg

Sarabakha, A., Fu, C., Kayacan, E. & Kumbasar, T. (2018). Type-2 Fuzzy Logic Controllers Made Even Simpler: From Design to Deployment in Real-Time for Quadcopter UAVs. IEEE Transactions on Industrial Electronics, 65(6), 5069-5077. https://doi.org/10.1109/TIE.2017.2767546

Kayacan, E., Sarabakha, A., Coupland, S., John, R. & Ahmadieh Khanesar, M. (2018). Type-2 Fuzzy Elliptic Membership Functions for Modeling Uncertainty. Engineering Applications of Artificial Intelligence, 70, 170-183. https://doi.org/10.1016/j.engappai.2018.02.004

Auken, E., Foged, N., Larsen, J. J., Lassen, K. V. T., Maurya, P. K., Møller Dath, S. & Eiskjær, T. T. (2019). tTEM — A towed transient electromagnetic system for detailed 3D imaging of the top 70 m of the subsurface. Geophysics, 84(1), E13-E22. https://doi.org/10.1190/geo2018-0355.1

Lausdahl, K. G., Bjerge, K., Bokhove, T., Groen, F. & Larsen, P. G. (2017). Transitioning from Crescendo to INTO-CPS. In J. S. Fitzgerald, P. W. V. Tran-Jørgensen & T. Oda (Eds.), The 15th Overture Workshop: New Capabilities and Applications for Model-based Systems Engineering: Proceedings (pp. 16-30). Newcastle University.

Liu, L., Yan, R-J., Maruvanchery, V., Kayacan, E., Chen, I-M. & Kong Tiong, L. (2017). Transfer learning on convolutional activation feature as applied to a building quality assessment robot. International Journal of Advanced Robotic Systems, 14(3), 1-12. https://doi.org/10.1177/1729881417712620

Larsen, O. V., Haase, J., Hansen, K. V., Brix, L. C. & Pedersen, C. F. (2003). Training brain retraction in a virtual reality environment. In Westwood, J.D. : Hoffman, H.M. : Mogel, G.T. : Phillips, R. : Robb, R.A. : Stredney, D. (eds.) (Ed.), Medicine Meets Virtual Reality 11 - NextMed: Health Horizon, MMVR 11, Newport Beach, CA, USA], [22-25 January: Studies in Health Technology and Informatics (94 ed., pp. 174-180).

Christensen, S., Jørgensen, R. & Egebirk, T. B. (2003). Trådløst netværk i landbruget. In Nyeste teknologi i markbruget. Danmarks JordbrugsForskning og Landbrugets Rådgivningscenter konference: Teknik i Landbruget 2003, Scandinavian Congress Center, Aarhus, 20.3.03. Bila (pp. 48-48)

Christensen, S., Jørgensen, R. & Christiansen, T. (2003). Trådløst netværk i landbruget: Nyeste teknologi i markbruget. In Ikke angivet (pp. 48). Dansk Landbrugsrådgivning og Danmarks JordbrugsForskning.

Duan, R., Fu, C. & Kayacan, E. (2017). Tracking-Recommendation-Detection. Engineering Applications of Artificial Intelligence, 64, 128-139. https://doi.org/10.1016/j.engappai.2017.05.012

Duan, R. (Producer), Fu, C. (Producer) & Kayacan, E. (Producer). (2017). Tracking-Recommendation-Detection. Pictures, Video and sound recordings (digital), YouTube. https://www.youtube.com/watch?v=L3XjGvsy4BA

Jensen, K. L., Pedersen, C. F. & Larsen, L. B. (2006). Towards useful and usable services in personal networks. In IEEE, 3rd Annual International Conference on Mobile and Ubiquitous System - Networking and Services (pp. 1-8). https://doi.org/10.1109/MOBIQ.2006.340415

Jensen, K., Laursen, M. S., M. Neerup, M., Skriver, M., Larsen, R. & Nyholm Jørgensen, R. (2016). Towards UAV contour flight over agricultural fields using RTK-GNSS and a Digital Elevation Model. Paper presented at International Conference on Agricultural Engineering 2016, Aarhus, Denmark. http://conferences.au.dk/uploads/tx_powermail/2016_cigr_towards_uav_contour_flight_over_agricultural_fields.pdf

Besson, M., Alison, J., Bjerge, K., Gorochowski, T. E., Høye, T. T., Jucker, T., Mann, H. M. R. & Clements, C. F. (2022). Towards the fully automated monitoring of ecological communities. Ecology Letters, 25(12), 2753-2775. https://doi.org/10.1111/ele.14123

Blanchet, V., Lochbrunner, S., Schmitt, M., P. Shaffer, J., Larsen, J. J., Z. Zgierski, M., Seideman, T. & Stolow, A. (2000). Towards disentangling coupled electronic-vibrational dynamics in ultrafast non-adiabatic processes. Faraday Discussions, 115, 33-48. https://doi.org/10.1039/b001138j

Kakavandi, F., Gomes, C., de Reus, R., Badstue, J., Jensen, J. L., Larsen, P. G. & Iosifidis, A. (2023). Towards Developing a Digital Twin for a Manufacturing Pilot Line: An Industrial Case Study. In E. Karaarslan, Ö. Aydin, Ü. Cali & M. Challenger (Eds.), Digital Twin Driven Intelligent Systems and Emerging Metaverse (pp. 39-64). Springer. https://doi.org/10.1007/978-981-99-0252-1_2

Jeppesen, J. H., Jacobsen, R. H., Nyholm Jørgensen, R. & Toftegaard, T. S. (2016). Towards Data-Driven Precision Agriculture using Open Data and Open Source Software. Paper presented at International Conference on Agricultural Engineering 2016, Aarhus, Denmark.

Christiansen, P., Sørensen, R., Skovsen, S., Jæger, C. D., Nyholm Jørgensen, R., Karstoft, H. & Steen, K. A. (2016). Towards Autonomous Plant Production using Fully Convolutional Neural Networks. Paper presented at International Conference on Agricultural Engineering 2016, Aarhus, Denmark. http://conferences.au.dk/uploads/tx_powermail/2016cigr-towardsautomousplantproductionusingfullyconvolutionalneuralnetworks.pdf

Larsen, M., Adam, M. S., Schultz, U. P. & Nyholm Jørgensen, R. (2014). Towards automatic consistency checking of software components in field robotics. In Proceedings of the Second International Conference on Robotics, Associated High-Technologies and Equipment for Agriculture and Forestry - RHEA 2014: New trends in mobile robotics, perception and actuation for agriculture and forestry (pp. 409-418)

Jensen, K., Larsen, M., Nielsen, S. H., Larsen, L. B., Olsen, K. S. & Nyholm Jørgensen, R. (2014). Towards an Open Software Platform for Field Robots in Precision Agriculture. Robotics, 3(2). https://doi.org/10.3390/robotics3020207

Kayacan, E., Kayacan, E., Ramon, H., Kaynak, O. & Saeys, W. (2014). Towards Agrobots: Trajectory Control of an Autonomous Tractor Using Type-2 Fuzzy Logic Controllers. IEEE - ASME Transactions on Mechatronics, 20(1), 287-298. https://doi.org/10.1109/TMECH.2013.2291874

Kayacan, E., Kayacan, E., Ramon, H. & Saeys, W. (2015). Towards agrobots: Identification of the yaw dynamics and trajectory tracking of an autonomous tractor. Computers and Electronics in Agriculture, 115, 78-87. https://doi.org/10.1016/j.compag.2015.05.012

Pedersen, C. F. (2016). Total Variation Optimization for Compressed Sensing Image Reconstruction. Faculty of Engineering and Science, Dept. of Computer Science, Aalborg University.

Passalis, N., Tsantekidis, A., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2017). Time-series Classification using Neural Bag-of-Features. Proceedings of the European Signal Processing Conference, 2017, 311-315. https://doi.org/10.23919/EUSIPCO.2017.8081217

Pedersen, M. N., Letschnik, J., Schelde, L., Karstoft, H., Schurig, F. & Walter, U. (2013). Three-dimensional radiation pattern measurement strategy for ground station antennas. International Journal of Satellite Communications and Networking, 31(1), 39-50. https://doi.org/10.1002/sat.1020

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

Sørensen, R. A., Rasmussen, J., Nielsen, J. & Nyholm Jørgensen, R. (2017). Thistle detection using convolutional neural networks. In 2017 EFITA WCCA Congress - European conference dedicated to the future use of ICT: Conference Proceedings (pp. 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

Jørgensen, R. (2002). The VTT line imaging spectrometer - Principles, Error sources and Calibration.

Gislum, R., Thomopoulos, S., Gyldengren, J. G., Mortensen, A. K. & Boelt, B. (2021). The Use of Remote Sensing to Determine Nitrogen Status in Perennial Ryegrass (Lolium perenne L.) for Seed Production. Nitrogen, 2(2), 229-243. https://doi.org/10.3390/nitrogen2020015

Mortensen, A. K., Gislum, R., Jørgensen, J. R. & Boelt, B. (2021). The Use of Multispectral Imaging and Single Seed and Bulk Near-Infrared Spectroscopy to Characterize Seed Covering Structures: Methods and Applications in Seed Testing and Research. Agriculture, 11(4), Article 301. https://doi.org/10.3390/agriculture11040301

Gaikwad, N., Liu, L., Griffiths, M. P., Vang, M. Ø., Grombacher, D. & Larsen, J. J. (2022). Thermal Model of the Apsu Transmitter for Lightweight and Compact Heat Sink Design. 11-13. Abstract from The 8th International Workshop on Magnetic Resonance Sounding, Strasbourg, France. https://mrs2021.sciencesconf.org/data/pages/proceedings_MRS2021_distrib_v2.pdf

Hansen, P. M. & Jørgensen, R. (2001). The Risø Cropassessor - An idea to a low-cost, robust, simple and modular measuring device based on existing technology for monitoring the spatial field crop variation. In Grenier, G. & Blackmore, S. (eds.), Agro Montpellier, Montpellier, France (pp. 37-42)

Jørgensen, R., Sørensen, C. A. G., Jacobsen, H., Kirk, K., Andersen, H. J. & Nantt, D. (2005). The potential of using robotics for data acquisition from multiple sensors within agricultural research. In Intelligent Systems in Design and Manufacturing VI. Proc. of SPIE Vol. 5999, 82-93. http://www.spiedl.org/

Christensen, S., Wu, O., Butcher, K., Hjort, N., Karstoft, H., Davis, S. & Østergaard, L. (2006). The Physiological Significance of the Tmax Parameter in Bolus Tracking MRI. Abstract from ISMRM 14th Annual Meeting, Seattle, United States.

Mortensen, A. K., Skovsen, S., Karstoft, H. & Gislum, R. (2019). The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation. Poster session presented at IEEE Conference on Computer Vision and Pattern Recognition 2019, Long Beach, California, United States.

Mortensen, A. K., Skovsen, S., Karstoft, H. & Gislum, R. (2019). The Oil Radish Growth Dataset for Semantic Segmentation and Yield Estimation. In Proceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2019 (pp. 2703-2710). Article 9025602 IEEE. Advance online publication. https://doi.org/10.1109/CVPRW.2019.00328

Mortensen, A. K. (Producer), Skovsen, S. (Producer), Karstoft, H. (Producer) & Gislum, R. (Producer). (2019). The Oil Radish Growth Dataset. Dataset

Iosifidis, A., Marami, E., Tefas, A., Pitas, I. & Lyroudia, K. (2015). The MOBISERV-AIIA Eating and Drinking multi-view database for vision-based assisted living. Journal of Information Hiding and Multimedia Signal Processing, 6(2), 254-273. http://bit.kuas.edu.tw/~jihmsp/2015/vol6/JIH-MSP-2015-02-008.pdf

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Revised 10.08.2023

AU Engineering