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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Shahrak Nadimi, E. & Jørgensen, R. N. (2012). MoDest GrassUp. (Patent No. DK2010/050334).

Jørgensen, R. N. & S. Nadimi, E. (2010, Feb 1). MoDest GrassUp.

Kayacan, E., Kayacan, E., Ramon, H. & Saeys, W. (2012). Model Predictive Control of the Yaw Dynamics of an Autonomous Tractor. In A. Peruzzi (Ed.), : Proceedings of the First International Conference on Robotics and Associated High-technologies and Equipment for Agriculture. Applications of automated systems and robotics for crop protection in sustainable precision agriculture (pp. 157-162). University of Pisa.

Eren, U., Prach, A., Bahadir Kocer, B., Rakovic, S. V., Kayacan, E. & Acikmese, B. (2017). Model Predictive Control in Aerospace Systems: Current State and Opportunities. AIAA Journal of Guidance, Control and Dynamics, 40(7), 1541-1566. https://doi.org/10.2514/1.G002507

Bochtis, D., Sørensen, C. A. G., Jørgensen, R. N. & Green, O. (2009). Modelling of material handling operations using controlled traffic. Biosystems Engineering, 103(4), 397-408. https://doi.org/10.1016/j.biosystemseng.2009.02.006

Hansen, K. V., Brix, L. C., Pedersen, C. F., Haase, J. & Larsen, O. V. (2004). Modelling of interaction between a spatula and a human brain. Medical Image Analysis, 8(1), 23-33. https://doi.org/10.1016/j.media.2003.07.001

Christensen, L. K., Bennedsen, B. S., Jørgensen, R. & Nielsen, H. (2004). Modelling nitrogen and phosphorus content at early growth stages in spring barley using spectral line scanning. Biosystems Engineering, 88(1), 19-24.

Pedersen, C. F., Brix, L. C., Hansen, K. V., Haase, J. & Larsen, O. V. (2002). Modeling interaction between a brain spatula and a human brain. Child's Nervous System, 18(5), 257-260. https://doi.org/10.1007/s00381-002-0581-4

Kayacan, E., Kayacan, E., Ramon, H. & Saeys, W. (2013). Modeling and Identification of the Yaw Dynamics of an Autonomous Tractor. In Control Conference (ASCC), 2013 9th Asian (pp. 1-6). IEEE. https://doi.org/10.1109/ASCC.2013.6606388

Larsen, J. J. (2016). Model-based subtraction of spikes from surface nuclear magnetic resonance data. Geophysics, 81(4), WB1-WB8. https://doi.org/10.1190/geo2015-0442.1

Dalgaard, E., Auken, E. & Larsen, J. J. (2012). Model-based noise cancelling of multichannel magnetic resonance sounding measurements. In Near Surface Geoscience 2012 European Association of Geoscientists and Engineers, EAGE. http://www.scopus.com/inward/record.url?scp=84898482260&partnerID=8YFLogxK

Feng, H., Gomes, C., Iosifidis, A. & Larsen, P. G. (2021). Model-based monitoring and state estimation for digital twins: The Kalman filter. In C. R. Martin, M. J. Blas & A. I. Psijas (Eds.), Annual Modeling and Simulation Conference (ANNSIM 2021) (pp. 1-2)

Larsen, J. J., Dalgaard, E. B. & Auken, E. (2012). Model-based cancelling of powerline harmonics in multichannel MRS recordings. Abstract from Magnetic Resonance in the Subsurface, Hannover, Germany.

Skovsen, S. K. (2021). Mixed Crop Mapping by Species Discrimination using Data Driven Computer Vision and Simulated Data. Århus Universitet.

Ma, X., J. Hegarty, P. & Larsen, J. J. (2018). Mitigation of Nonlinear Distortion in Sound Zone Control by Constraining Individual Loudspeaker Driver Amplitudes. I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings, 2018, 456-460. https://doi.org/10.1109/ICASSP.2018.8462135

Grombacher, D., Liu, L., Osterman, G. K. & Larsen, J. J. (2021). Mitigating Narrowband Noise Sources Close to the Larmor Frequency in Surface NMR. IEEE Geoscience and Remote Sensing Letters, 18(8), 1376-1380. https://doi.org/10.1109/LGRS.2020.3000639

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

Gautam, C., Tiwari, A. & Iosifidis, A. (2019). Minimum Variance-Embedded Multi-layer Kernel Ridge Regression for One-class Classification. In S. Sundaram (Ed.), Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018 (pp. 389-396). Article 8628692 IEEE. https://doi.org/10.1109/SSCI.2018.8628692

Iosifidis, A., Tefas, A. & Pitas, I. (2013). Minimum Class Variance Extreme Learning Machine for Human Action Recognition. IEEE Transactions on Circuits and Systems for Video Technology, 23(11), 1968-1979. https://doi.org/10.1109/TCSVT.2013.2269774

Alvarez Tunon, O., Kanner, H., Ribeiro Marnet, L., Pham, X. H., Sejersen, J. L. F., Brodskiy, Y. & Kayacan, E. (2023). MIMIR-UW: A Multipurpose Synthetic Dataset for Underwater Navigation and Inspection. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 6141-6148). IEEE. https://doi.org/10.1109/IROS55552.2023.10341436

Ntakaris, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Mid-price prediction based on machine learning methods with technical and quantitative indicators. PLOS ONE, 15(6 June), Article e0234107. https://doi.org/10.1371/journal.pone.0234107

Lochbrunner, S., Larsen, J. J., Shaffer, J. P., Schmitt, M., Schultz, T., Underwood, J. G. & Stolow, A. (2000). Methods and applications of femtosecond time-resolved photoelectron spectroscopy. Journal of Electron Spectroscopy and Related Phenomena, 112(1-3), 183-198. https://doi.org/10.1016/S0368-2048(00)00212-7

Jørgensen, R., Sørensen, C. A. G., Søgaard, H. T., Kristensen, K., Green, O. & Christensen, S. (2007). Methodology for a Labor Extensive and Semi-Automated Field Trial Design Using Autoguidance and Comventional Machinery. In J. V. Stafford (Ed.), Ikke angivet (pp. 441-449). Wageningen Academic Publishers.

Nyholm Jørgensen, R., Steen, K. A. & Olesen, C. R. (2015). Method for removing animals from a field. (Patent No. DK2015/050155).

Christiansen, M. P. & Nyholm Jørgensen, R. (2015). Method for recording and predicting position data for a selfpropelled wheeled vehicle, and delivery or pick up system comprising a self-propelled, self-guided wheeled vehicle. (Patent No. DK178276 (B1) ).

Jørgensen, R. N., Green, O., Gislum, R. & Sørensen, C. A. G. (2010). Method for optimizing harvesting of crops. (Patent No. WO/2010/003421). http://www.wipo.int/pctdb/en/wo.jsp?WO=2010003421&IA=DK2009050150&DISPLAY=DESC

Jørgensen, R. N., Green, O., Sørensen, C. A. G. & Gislum, R. (2008). Method for optimizing harvesting of crops. (Patent No. PA 2008 00955).

S. Nadimi, E., Jørgensen, R. N. & Oudshoorn, F. W. (2011). Method and system for estimating herbage uptake of an animal. (Patent No. PCT/DK2010/050334).

Nyholm Jørgensen, R. (2017). Metatilgangen til Deep Learning. Pictures, Video and sound recordings (digital), YouTube. https://www.youtube.com/watch?v=moLU3QvWIRM&t=355s

Iosifidis, A., Tefas, A. & Pitas, I. (2015). Merging Linear Discriminant Analysis with Bag of Words model for Human Action Recognition. In Image Processing (ICIP), 2015 IEEE International Conference on (pp. 832-836). IEEE. https://doi.org/10.1109/ICIP.2015.7350916

Lang, X., Rehman, N. U., Zhang, Y., Xie, L. & Su, H. (2020). Median ensemble empirical mode decomposition. Signal Processing, 176, Article 107686. https://doi.org/10.1016/j.sigpro.2020.107686

Kicanaoglu, B., Iosifidis, A. & Gabbouj, M. (2016). Maximum Margin Binary Classifiers using Intrinsic and Penalty graphs. In 2016 24th European Signal Processing Conference, EUSIPCO 2016 (pp. 2270-2274). Article 7760653 IEEE. https://doi.org/10.1109/EUSIPCO.2016.7760653

Tsapanos, N., Iosifidis, A. & Pitas, I. (2015). Mathematical preliminaries: graphs and matrices. In I. Pitas (Ed.), Graph-Based Social Media Analysis CRC Press.

Bajovic, D., Bakhtiarnia, A., Bravos, G., Brutti, A., Burkhardt, F., Cauchi, D., Chazapis, A., Cianco, C., Dall'Asen, N., Delic, V., Dimou, C., Djokic, D., Escobar-Molero, A., Esterle, L., Eyben, F., Farella, E., Festi, T., Geromitsos, A., Giakoumakis, G. ... Zammit, J. (2021). MARVEL: Multimodal Extreme Scale Data Analytics for Smart Cities Environments. In 2021 International Balkan Conference on Communications and Networking, BalkanCom 2021 (pp. 143-147). IEEE. https://doi.org/10.1109/BalkanCom53780.2021.9593258

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. In J. V. Stafford (Ed.), Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019 (pp. 231-237). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-888-9_28

Jensen, B.-E., Andersen, H. J. & Jørgensen, R. (2004). Markrobotten arbejder. Agrologisk, 10, 12-13.

Green, O. & Jørgensen, R. (2007). Markforsøg med hundredvis af parceller. Bovilogisk, (5), 25.

Dobbs, A. M., Goldsmith, A. S., Ginn, D., Skovsen, S. K., Bagavathiannan, M. V., Mirsky, S. B., Reberg-Horton, C. S. & Leon, R. G. (2024). Mapping predicted biomass in cereal rye using 3D imaging and geostatistics. Weed Science, 72(5), 553-561. https://doi.org/10.1017/wsc.2024.62

Larsen, J. J., Dalgaard, E. B., Christiansen, P. & Auken, E. (2015). Mapping of electromagnetic noise in a magnetic resonance sounding context. In ASEG Extended Abstracts - 24th International Geophysical Conference and Exhibition: Geophysics and Geology Together for Discovery (Vol. 2015/1). CSIRO Publishing. https://doi.org/10.1071/ASEG2015ab241

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

Chavez Plascencia, A. & Karstoft, H. (2014). Map Building based on a Xtion Pro Live RGBD and a Laser Sensors. Journal of Information Technology & Software Engineering, 4, Article 126. https://doi.org/10.4172/2165-7866.1000126

Magris, M., Shabani, M. & Iosifidis, A. (2024). Manifold Gaussian Variational Bayes on the Precision Matrix. Neural Computation, 36(9), 1744-1798. https://doi.org/10.1162/neco_a_01686

Nousi, P., Tsantekidis, A., Passalis, N., Ntakaris, A., Kanniainen, J., Tefas, A., Gabbouj, M. & Iosifidis, A. (2019). Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data. IEEE Access, 7, 64722 - 64736 . Article 8713851. https://doi.org/10.1109/ACCESS.2019.2916793

Bording, T. S., Asif, M. R., Barfod, A. S., Larsen, J. J., Zhang, B., Grombacher, D. J., Christiansen, A. V., Engebretsen, K. W., Pedersen, J. B., Maurya, P. K. & Auken, E. (2021). Machine learning based fast forward modelling of ground-based time-domain electromagnetic data. Journal of Applied Geophysics, 187, Article 104290. https://doi.org/10.1016/j.jappgeo.2021.104290

Chumachenko, K., Mannisto, A., Iosifidis, A. & Raitoharju, J. (2020). Machine Learning Based Analysis of Finnish World War II Photographers. IEEE Access, 8, 144184-144196. Article 9159591. https://doi.org/10.1109/ACCESS.2020.3014458

Islam, M. T., Khan, H. A., Naveed, K., Nauman, A., Gulfam, S. M. & Kim, S. W. (2023). LUVS-Net: A Lightweight U-Net Vessel Segmentor for Retinal Vasculature Detection in Fundus Images. Electronics, 12(8), Article 1786. https://doi.org/10.3390/electronics12081786

Shabani, M. & Iosifidis, A. (2020). Low-Rank Temporal Attention-Augmented Bilinear Network for financial time-series forecasting. In 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (pp. 2156-2161). Article 9308440 IEEE. https://doi.org/10.1109/SSCI47803.2020.9308440

Liu, L., Grombacher, D. J., Auken, E. & Larsen, J. J. (2018). Low noise, multichannel surface NMR receiver system with wireless connections to receiver coils. Abstract from First Australian Exploration Geoscience Conference, Sydney, Australia. http://www.publish.csiro.au/ex/pdf/ASEG2018abT7_1H

Alvarez Tunon, O., Brodskiy, Y. & Kayacan, E. (2023). Loss it right: Euclidean and riemannian metrics in learning-based visual odometry. In ISR Europe 2023: 56th International Symposium on Robotics, in cooperation with Fraunhofer IPA September 26 – 27, 2023 in Stuttgart (pp. 107-111). VDE Verlag GmbH. https://ieeexplore.ieee.org/abstract/document/10363060

Klausen, K. C., Pagels, K. Ø., Bjerre, J. (Ed.) & Pedersen, C. F. (Ed.) (2019). LoRa and LoRaWAN Case Studies. European Regional Development Fund and Central Denmark Region.

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