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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Li, L., Looney, D., Park, C., Rehman, N. U. & Mandic, D. P. (2011). Power independent EMG based gesture recognition for robotics. In 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE. https://doi.org/10.1109/iembs.2011.6090036

Grombacher, D. J., Larsen, J. J. & Auken, E. (2016). Potential for Square Wave Transmitters in Surface NMR. In Near Surface Geoscience 2016: 22nd European Meeting of Environmental and Engineering Geophysics (Vol. 2016). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.201602008

Li, C., Bozorgtabar, B., Ping, Y., Huang, P. & Qin, J. (2025). Positive Semi-definite Latent Factor Grouping-Boosted Cluster-reasoning Instance Disentangled Learning for WSI Representation.

Christiansen, P., Kragh, M. F., Steen, K. A., Karstoft, H. & Nyholm Jørgensen, R. (2017). Platform for evaluating sensors and human detection in autonomous mowing operations. Precision Agriculture, 18(3), 350-365. https://doi.org/10.1007/s11119-017-9497-6

Dyrmann, M., Karstoft, H. & Midtiby, H. S. (2016). Plant species classification using deep convolutional neural network. Biosystems Engineering, 151(November), 72-80. https://doi.org/10.1016/j.biosystemseng.2016.08.024

Nyholm Jørgensen, R. (2020). Plantekongres 2020 - RoboWeedMaps præsenterer: Flere muligheder med digital ukrudtsgenkendelse. Pictures, Video and sound recordings (digital) https://www.youtube.com/watch?v=HEsJ9k1SJYM

Dyrmann, M., Mortensen, A. K., Midtiby, H. S. & Nyholm Jørgensen, R. (2016). Pixel-wise classification of weeds and crops in images by using a Fully Convolutional neural network. Paper presented at International Conference on Agricultural Engineering 2016, Aarhus, Denmark. http://conferences.au.dk/uploads/tx_powermail/cigr2016paper_semanticsegmentation.pdf

Gislum, R. & Nyholm Jørgensen, R. (2016). Pilotprojekt vedr. billedanalyse på golfbaner med henblik på reduktion i pesticidforbruget og implementering af IPM.

Ma, X., J. Hegarty, P., Abildgaard Pedersen, J., Johansen, L. G. & Larsen, J. J. (2016). Personal Sound Zones: The significance of loudspeaker driver nonlinear distortion. 311-315. Paper presented at 2016 AES International Conference on Sound Field Control, Guildford, United Kingdom. https://doi.org/10.1109/ICASSP.2016.7471687

Ferrarini, B., Ehsan, S., Leonardis, A., Rehman, N. U. & McDonald-Maier, K. D. (2018). Performance Characterization of Image Feature Detectors in Relation to the Scene Content Utilizing a Large Image Database. IEEE Access, 6, 8564-8573. https://doi.org/10.1109/access.2018.2795460

Mahapatra, D., Bozorgtabar, B., Thiran, J.-P. & Shao, L. (2020). Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation.

Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2020). Parallelized Hybrid Bloch Solver for Surface Nuclear Magnetic Resonance. Abstract from Near Surface Geoscience 2020. https://doi.org/10.3997/2214-4609.202020063

Dalgaard, E. B., Auken, E. & Larsen, J. J. (2012). Optimized Wiener filtering with the Numis Poly system. Abstract from Magnetic Resonance in the Subsurface, Hannover, Germany.

Kamble, K., Jensen, C. E. H. & Larsen, J. J. (2024). Optimized Suppression of VLF Radio Noise in Time-lapse Transient Electromagnetic Data. Abstract from AGU Fall meeting 2024, Washington DC, United States.

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

Nyholm Jørgensen, R. (2016). OptiMek Temadag - En fremtid med droner i landbruget. Pictures, Video and sound recordings (digital), YouTube. https://www.youtube.com/watch?v=vZii3S9QP_s&feature=youtu.be

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

McLachlan, P. J., Khare, S. K., Grombacher, D., Larsen, J. J., A. Christiensen, A. & Luria, J. C. Z. (2022). On The Presence of Correlated Noise in Transient Electromagnetic (Tem) Monitoring Data. 1-5. Abstract from NSG2022 28th European Meeting of Environmental and Engineering Geophysics, Belgrade , Serbia. https://doi.org/10.3997/2214-4609.202220119

McLachlan, P. J., Khare, S. K., Grombacher, D., Larsen, J. J., Christensen, A. & Zamora Luria, J. C. (2022). On The Presence of Correlated Noise in Transient Electromagnetic (Tem) Monitoring Data. In NSG2022 28th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202220119

Teimouri, N., Omid, M., Mollazade, K., Mousazadeh, H., Alimardani, R. & Karstoft, H. (2018). On-line separation and sorting of chicken portions using a robust vision-based intelligent modelling approach. Biosystems Engineering, 167, 8-20. https://doi.org/10.1016/j.biosystemseng.2017.12.009

Sarabakha, A. & Kayacan, E. (2019). Online deep learning for improved trajectory tracking of unmanned aerial vehicles using expert knowledge. In 2019 International Conference on Robotics and Automation, ICRA 2019 (pp. 7727-7733). Article 8794314 IEEE. https://doi.org/10.1109/ICRA.2019.8794314

Sarabakha, A. & Kayacan, E. (2020). Online Deep Fuzzy Learning for Control of Nonlinear Systems Using Expert Knowledge. IEEE Transactions on Fuzzy Systems, 28(7), 1492-1503. https://doi.org/10.1109/TFUZZ.2019.2936787

Sarabakha, A., Qiao, Z., Ramasamy, S. & Suganthan, P. N. (2023). Online Continual Learning for Control of Mobile Robots. In 2023 International Joint Conference on Neural Networks (IJCNN) (pp. 1) https://doi.org/10.1109/IJCNN54540.2023.10191188

Jørgensen, R. N. & Maagaard, J. (2008). Omni rotational driving and steering wheel. (Patent No. WO2008138346). http://v3.espacenet.com/publicationDetails/biblio?KC=A1&date=20081120&NR=2008138346A1&DB=EPODOC&locale=en_EP&CC=WO&FT=D

Grombacher, D., Griffiths, M. P., Vang, M. Ø., Kass, M. A. & Larsen, J. J. (2024). Observation of spikelets in steady-state surface nuclear magnetic resonance data. Geophysics, 89(2), J1-J8. https://doi.org/10.1190/GEO2023-0145.1

Bjerge, K., Frigaard, C. E. & Karstoft, H. (2023). Object Detection of Small Insects in Time-Lapse Camera Recordings. Sensors, 23(16), Article 7242. https://doi.org/10.3390/s23167242

Hansen, M. K., Nyholm Jørgensen, R. & Pedersen, H. (2015). Object Detection and Terrain Classification in Agricultural Fields using 3D Lidar Data. In Computer Vision Systems: 10th International Conference, ICVS 2015, Proceedings (Vol. 9163, pp. 188-197). Springer. https://doi.org/10.1007/978-3-319-20904-3_18

Christensen, L. K. & Jørgensen, R. (2004). Nutrient stress discrimination of N, P, and K deficiencies in barley utilising multi-band reflection at sub-leaf scale. In CIGR2004, Beijing, China. Collection of Extent Abstracts, Vol. 1, p. I-63. Paper on CD: ISBN 7-80167-707-2/ (pp. 537) https://www.academia.edu/67063468/Nutrient_stress_discrimination_of_N_P_and_K_deficiencies_in_barley_utilising_multi_band_reflection_at_sub_leaf_scale?uc-g-sw=67063526

Sarabakha, A., Imanberdiyev, N., Kayacan, E., Ahmadieh Khanesar, M. & Hagras, H. (2017). Novel Levenberg-Marquardt Based Learning Algorithm for Unmanned Aerial Vehicles. Information Sciences, 417, 361-380. https://doi.org/10.1016/j.ins.2017.07.020

Dormann, F., Frisk, O., Andersen, L. N. & Pedersen, C. F. (2021). Not All Noise Is Accounted Equally: How Differentially Private Learning Benefits From Large Sampling Rates. In 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing, MLSP 2021 IEEE. https://doi.org/10.1109/MLSP52302.2021.9596307

Hemakom, A., Ahrabian, A., Looney, D., Rehman, N. U. & Mandic, D. P. (2015). Nonuniformly sampled trivariate empirical mode decomposition. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) IEEE. https://doi.org/10.1109/icassp.2015.7178660

Ma, X., Hegarty, P. J., Jørgensen, K. F. & Larsen, J. J. (2019). Nonlinear distortion reduction in sound zones by constraining individual loudspeaker control effort. Journal of the Audio Engineering Society, 67(9), 641-654. https://doi.org/10.17743/jaes.2019.0015

Rasmussen, S., Skovgaard Nyboe, N., Mai, S. & Larsen, J. J. (2017). Noise properties of Fourier deconvolution for time-domain electromagnetic soundings. Geophysics, 82(5), E257-E266. https://doi.org/10.1190/geo2016-0588.1

Larsen, J. J., Dalgaard, E. B. & Auken, E. (2013). Noise Cancelling of Multichannel MRS Signals with a Time Dependent Harmonic Model. Poster session presented at AGU Fall Meeting, San Francisco, United States.

Larsen, J. J., Dalgaard, E. B. & Auken, E. (2013). Noise cancelling of MRS signals combining model-based removal of powerline harmonics and multichannel Wiener filtering. Geophysical Journal International, 196(2), 828-836. https://doi.org/10.1093/gji/ggt422

Dalgaard, E., Auken, E. & Larsen, J. J. (2011). Noise Cancellation of Multichannel Magnetic Resonance Sounding Measurements with Wiener and Adaptive Filters. Abstract from EAGE Near Surface 2011, Leiceister, United Kingdom. http://www.earthdoc.org/publication/publicationdetails/?publication=53995

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.

Kremer, T., Larsen, J. J. & Nguyen, F. (2018). New Processing Schemes for the Removal of Harmonic Noise from SNMR Signals in Complex Multi-Frequency Noise Environments. In 24th European Meeting of Environmental and Engineering Geophysics European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.201802552

Böttner, C., Jakobsen, F. W., Nielsen, T., Winsborrow, M., Polteau, S., Mazzini, A., Planke, S., Andresen, K. J., Millinge, O. J. S., Asif, M. R., Laberg, J. S., Hopper, J., Myklebust, R. & Seidenkrantz, M. S. (2025). Natural hydrocarbon seepage at the Northeast Greenland continental shelf. Communications Earth and Environment, 6(1), Article 879. https://doi.org/10.1038/s43247-025-02932-8

Naveed, K., de Freitas, B. N. & Pauwels, R. (2025). Naada: A Noise-Aware Attention Denoising Autoencoder for Dental Panoramic Radiographs.

Jørgensen, R., Jørgensen, B. J. & Nielsen, N. E. (1998). N2O emission immediately after rainfall in a rye stubble field. Soil Biology & Biochemistry, 30(4), 545-546.

Jørgensen, R. & Jørgensen, B. J. (1998). N2O emission from Miscanthus, rye and oilseed rape in relation to the net CO2-displacement. In Wörgetter, M. & Jørgensen, U. (eds.), Environmental aspects of energy crop production. Proc. IEA workshop, Brassimone, Italy, 1997. Report from BLT.

Jørgensen, R., Jørgensen, B. J., Nielsen, N. E., Maag, M. & Lind, A.-M. (1997). N2O emission from energy crop fields with Miscanthus Giganteus and winter rye. Atmospheric Environment, 31, 2899-2904.

Jørgensen, R. N., Jørgensen, B. J., Nielsen, N. E., Maag, M. M. & Lind, A.-M. (1997). N2O emission from energy crop fields of Miscanthus " giganteus" and winter rye. Atm. Environ, 31, 2899-2904.

Jørgensen, B. J. & Jørgensen, R. (1996). N2O emission from energy crop fields.

Rehman, N. U. & Aftab, H. (2019). Multivariate Variational Mode Decomposition. IEEE Transactions on Signal Processing, 67(23), 6039-6052. Article 8890883. https://doi.org/10.1109/TSP.2019.2951223

Naveed, K., Mukhtar, S. & Ur Rehman, N. (2021). Multivariate Signal Denoising Based on Generic Multivariate Detrended Fluctuation Analysis. In 2021 IEEE Statistical Signal Processing Workshop, SSP 2021 (pp. 441-445). IEEE. https://doi.org/10.1109/SSP49050.2021.9513823

Ahmed, M. U., Rehman, N., Looney, D., Rutkowski, T. M., Kidmose, P. & Mandic, D. P. (2012). Multivariate entropy analysis with data-driven scales. In 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 3901-3904). IEEE. https://doi.org/10.1109/icassp.2012.6288770, https://doi.org/10.1109/ICASSP.2012.6288770

ur Rehman, N., Ehsan, S., Abdullah, S. M. U., Akhtar, M. J., Mandic, D. P. & McDonald-Maier, K. D. (2015). Multi-Scale pixel-based image fusion using multivariate empirical mode decomposition. Sensors (Switzerland), 15(5), 10923-10947. https://doi.org/10.3390/s150510923

Naveed, K., Shaukat, B., Ehsan, S., Mcdonald-Maier, K. D., Rehman, N. U. & Baghaie, A. (Ed.) (2019). Multiscale image denoising using goodness-of-fit test based on EDF statistics. PLoS One, 14(5), e0216197. https://doi.org/10.1371/journal.pone.0216197

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Revised 13.11.2025

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