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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Larsen, J. J. & Behroozmand, A. A. (2015). Surface-NMR in High Noise Areas. Poster-session præsenteret på The 21st European Meeting of Environmental and Engineering Geophysics, Turin, Italien.

Larsen, J. J. & Behroozmand, A. A. (2015). Processing of Surface-NMR Data From Sites With High Noise. Abstract fra AGU Fall Meeting 2015, San Fransisco, USA. https://agu.confex.com/agu/fm15/meetingapp.cgi/Paper/69401

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

Larsen, J. J. & Behroozmand, A. A. (2016). Processing of surface-nuclear magnetic resonance data from sites with high noise levels. Geophysics, 81(4), WB75-WB83. https://doi.org/10.1190/geo2015-0441.1

Larsen, J. J. (2016). Despiking of Surface-NMR Data Using a Model-based Approach. I Near Surface Geoscience 2016 : 22nd European Meeting of Environmental and Engineering Geophysics (Bind 2016). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.201602068

Larsen, P. G., Kristiansen, E. L., Bennedsen, J. & Bjerge, K. (2017). Enhancing non-technical skills by a multidisciplinary engineering summer school. European Journal of Engineering Education, 42(6), 1076-1096. https://doi.org/10.1080/03043797.2016.1261278

Larsen, J. J., Liu, L., Grombacher, D. J. & Auken, E. (2018). Removal of Co-frequency Powerline Harmonics from Multichannel Surface NMR Data. I 23rd European Meeting of Environmental and Engineering Geophysics 2017 (Bind 15, s. 53-57). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.201702040

Larsen, J. J., Liu, L., Grombacher, D. J., Osterman, G. K. & Auken, E. (2018). Apsu - a new surface NMR instrument.. C01. Afhandling præsenteret på 7th International Workshop on Magnetic Resonance, Jilin, Kina.

Larsen, D., Skovsen, S., Steen, K. A., Grooters, K., Eriksen, J., Green, O. & Nyholm Jørgensen, R. (2018). Autonomous Mapping of Grass-Clover Ratio Based on Unmanned Aerial Vehicles and Convolutional Neural Networks. I Proceedings of the 14th International Conference on Precision Agriculture Artikel 5107 International Society of Precision Agriculture. https://www.ispag.org/proceedings/?action=download&item=5107

Larsen, J. J., Liu, L., Grombacher, D. & Auken, E. (2017). Removal of Co-Frequency powerline harmonics from multichannel Surface NMR Data. I 23rd European Meeting of Environmental and Engineering Geophysics European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.201702040

Larsen, D., Steen, K. A., Skovsen, S., Grooters, K., Eriksen, J., Nyholm Jørgensen, R., Dyrmann, M. & Green, O. (2018). Semantic Segmentation of Clover-Grass Images using Images from Commercially Available Drones. 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. 110). Wageningen University. https://doi.org/10.18174/471678

Larsen, J. J., Liu, L., Grombacher, D., Osterman, G. & Auken, E. (2019). Apsu - A new surface nmr instrument for hydrogeophysics. Afhandling præsenteret på 25th European Meeting of Environmental and Engineering Geophysics, Held at Near Surface Geoscience Conference and Exhibition 2019, NSG 2019, The Hague, Holland.

Larsen, J. J., Liu, L., Grombacher, D., Osterman, G. K. & Auken, E. (2020). Apsu — A new compact surface nuclear magnetic resonance system for groundwater investigation. Geophysics, 85(2), JM1-JM11. https://doi.org/10.1190/geo2018-0779.1

Larsen, J. J., Pedersen, S. S., Foged, N. & Auken, E. (2021). Suppression of very low frequency radio noise in transient electromagnetic data with semi-tapered gates. Geoscientific Instrumentation, Methods and Data Systems, 10(1), 81-90. Artikel 8. https://doi.org/10.5194/gi-10-81-2021

Larsen, J. J., Langhof, R. B., Kjær, M. W., Vang, M., Liu, L., Griffiths, M. & Grombacher, D. (2022). Efficient processing of surface NMR data with spectral analysis. Geophysical Journal International, 229(1), 286-298. https://doi.org/10.1093/gji/ggab472

Larsen, J. J., Lévy, L. & Asif, M. R. (2022). Removal of powerline noise in geophysical data sets with a scientific machine-learning based approach. IEEE Transactions on Geoscience and Remote Sensing, 60, Artikel 5923410. https://doi.org/10.1109/TGRS.2022.3223737

Larsen, J. J., Kass, M. A., Grombacher, D. & Griffiths, M. P. (2024). Feasibility of Surface Nuclear Magnetic Resonance With Absurdly Long Excitation Pulses. Geophysical Research Letters, 51(20), Artikel e2024GL110826. https://doi.org/10.1029/2024GL110826

Larsen, J. J., Kass, A., Grombacher, D. & Griffiths, M. P. (2024). Surface NMR with Very Long Transmitter Pulses. Abstract fra AGU Fall meeting 2024, Washington DC, USA.

Larsen, J. J. (2000). Laser induced alignment of neutral molecules. Institut for Fysik og Astronomi, Aarhus Universitet.

Larsen, J. J., Griffiths, M., Vang, M., Liu, L. & Grombacher, D. (2021). Apsu - A compact surface NMR instrument for groundwater investigations. I SEG Technical Program Expanded Abstracts 2021 (s. 3135-3139). Society of Exploration Geophysicists. https://doi.org/10.1190/segam2021-3582046.1

Larsen, J. J., Asif, M. R. & Rafiei Foroushani, M. (2025). Benchmarking deep learning models for wetland mapping in Denmark using high-resolution earth observation data. Abstract fra EGU General Assembly 2025, Vienna, Østrig. https://doi.org/10.5194/egusphere-egu25-4365

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

Lakshminarayanan, S., Duecker, D., Sarabakha, A., Ganguly, A., Takayama, L. & Haddadin, S. (2024). Estimation of External Force acting on Underwater Robots. I 2024 IEEE 20th International Conference on Automation Science and Engineering, CASE 2024 (s. 3125-3131). IEEE. https://doi.org/10.1109/CASE59546.2024.10711608

Kusk, K., Nielsen, D. B., Thylstrup, T., Rasmussen, N. H., Jørvang, J., Pedersen, C. F. & Wagner, S. R. (2012). Lessons Learned From a Lightweight Context-Aware System for Achieving Reliable Home Blood Pressure Self-Measurements. Afhandling præsenteret på NordiCHI 2012, The Nordic Conference on Human-Computer Interaction, Copenhagen, Danmark.

Kusk, K., Nielsen, D. B., Thylstrup, T., Rasmussen, N. H., Jørvang , J., Pedersen, C. F. & Wagner, S. R. (2013). Feasibility of using a lightweight context-aware system for facilitating reliable home blood pressure self-measurements. I Proceedings of the 2013 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops: PervasiveHealth 2013 (s. 236-239) https://doi.org/10.4108/icst.pervasivehealth.2013.252107

Kumar, K., Chakraborty, S., Mahapatra, D., Bozorgtabar, B. & Roy, S. (2025). Self-Supervised Anomaly Segmentation via Diffusion Models with Dynamic Transformer UNet. I Proceedings - 2025 IEEE Winter Conference on Applications of Computer Vision, WACV 2025 (s. 7928-7938). IEEE. https://doi.org/10.1109/WACV61041.2025.00770

Kryger, P. & Bjerge, K. (2019). Tælling af varroamider. I Varroatolerance i Danmark : de første skridt februar 2019 (s. 28-31). Danmarks Biavlerforening.

Kristensen, K. & Jørgensen, R. N. (2007). Analysis of trials with many replicates where treatments are randomised into rows and blocks. I H. Bleiholder & H.-P. Piepgo (red.), Proceedings of the International Symposium (s. 92-97). University of Hohenheim.

Kristensen, M. V., Ahrendt, P., Lindballe, T. B., Nielsen, O. H. A., Kylling, A. P., Karstoft, H., Imparato, A., Rigau, L. H., Stadler, B., Stapelfeldt, H. & Keiding, S. R. (2012). Motion analysis of optically trapped particles and cells using 2D Fourier analysis. Optics Express, 20(3), 1953-1962. https://doi.org/10.1364/OE.20.001953

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. I 24th European Meeting of Environmental and Engineering Geophysics European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.201802552

Kremer, T., Juul Larsen, J. & Nguyen, F. (2019). Processing harmonic EM noise with multiple or unstable frequency content in surface NMR surveys. Geophysical Journal International, 219(2), 753-775. https://doi.org/10.1093/gji/ggz307

Kremer, T., Irons, T., Müller-Petke, M. & Juul Larsen, J. (2022). Review of Acquisition and Signal Processing Methods for Electromagnetic Noise Reduction and Retrieval of Surface Nuclear Magnetic Resonance Parameters. Surveys in Geophysics, 43(4), 999-1053. https://doi.org/10.1007/s10712-022-09695-3

Kragh, M. F., Bjerge, K. & Ahrendt, P. (2016). 3D impurity inspection of cylindrical transparent containers. Measurement Science and Technology, 28(1), Artikel 017002 . https://doi.org/10.1088/1361-6501/28/1/017002

Kragh, M. F., Christiansen, P., Laursen, M. S., Larsen, M., Steen, K. A., Green, O., Karstoft, H. & Jørgensen, R. N. (2017). FieldSAFE: Dataset for Obstacle Detection in Agriculture. Sensors, 17(11), Artikel 2579. https://doi.org/10.3390/s17112579

Kragh, M. F., Rimestad, J., Berntsen, J. & Karstoft, H. (2019). Automatic morphological grading of human blastocysts with time-lapse imaging and artificial intelligence. Abstract fra ESHRE, Vienna, Østrig. https://www.eshre.eu/ESHRE2019/Programme/Searchable#!abstractdetails/0000573820

Kragh, M. F., Rimestad, J., Berntsen, J. & Karstoft, H. (2019). Automatic grading of human blastocysts from time-lapse imaging. Computers in Biology and Medicine, 115, Artikel 103494. https://doi.org/10.1016/j.compbiomed.2019.103494

Kragh, M. F. & Karstoft, H. (2021). Embryo selection with artificial intelligence: how to evaluate and compare methods? Journal of Assisted Reproduction and Genetics, 38(7), 1675-1689. https://doi.org/10.1007/s10815-021-02254-6

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

Korthals, T., Kragh, M. F., Christiansen, P., Karstoft, H., Nyholm Jørgensen, R. & Rückert, U. (2018). Multi-Modal Detection and Mapping of Static and Dynamic Obstacles in Agriculture for Process Evaluation. Frontiers in Robotics and AI, 5(MAR), Artikel 28. https://doi.org/10.3389/frobt.2018.00028

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

Kjaer-Rasmussen, A., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2022). Fast removal of powerline harmonic noise from surface NMR datasets using a projection-based approach on graphical processing units. IEEE Geoscience and Remote Sensing Letters, 19, Artikel 8024005. https://doi.org/10.1109/LGRS.2021.3118064

Khawaja, A., Khan, T. M., Naveed, K., Naqvi, S. S., Rehman, N. U. & Nawaz, S. J. (2019). An Improved Retinal Vessel Segmentation Framework Using Frangi Filter Coupled With the Probabilistic Patch Based Denoiser. IEEE Access, 7, 164344-164361. https://doi.org/10.1109/access.2019.2953259

Khare, S. K., McLachlan, P., Maurya, P. K. & Larsen, J. J. (2024). An optimized and hybrid gating scheme for the suppression of very low-frequency radios in transient electromagnetic systems. Geoscientific Instrumentation, Methods and Data Systems, 13(1), 27-41. https://doi.org/10.5194/gi-13-27-2024

Khan, T. M., Khan, M. A. U., Rehman, N. U., Naveed, K., Afridi, I. U., Naqvi, S. S. & Raazak, I. (2022). Width-wise vessel bifurcation for improved retinal vessel segmentation. Biomedical Signal Processing and Control, 71(Part A), Artikel 103169. https://doi.org/10.1016/j.bspc.2021.103169

Khan, N., Baig, F., Nawaz, S., Rehman, N. U. & Sharma, S. (2016). Analysis of Power Quality Signals Using an Adaptive Time-Frequency Distribution. Energies, 9(11), 933. https://doi.org/10.3390/en9110933

Khalid, S. S., Rehman, N. U., Abrar, S. & Mihaylova, L. (2018). Robust Bayesian Filtering Using Bayesian Model Averaging and Restricted Variational Bayes. I 2018 21st International Conference on Information Fusion (FUSION) IEEE. https://doi.org/10.23919/icif.2018.8455608

Khalid, S. S., Rehman, N. U. & Abrar, S. (2017). Robust stochastic integration filtering for nonlinear systems under multivariate t -distributed uncertainties. Signal Processing, 140, 53-59. https://doi.org/10.1016/j.sigpro.2017.05.007

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

Kass, M. A., Christiansen, A. V., Auken, E. & Larsen, J. J. (2021). Efficient reduction of powerline signals in magnetic data acquired from a moving platform. IEEE Transactions on Geoscience and Remote Sensing, 59(8), 7137-7146. Artikel 9246269. https://doi.org/10.1109/TGRS.2020.3029658

Kass, M. A., Auken, E., Larsen, J. J. & Christiansen, A. V. (2021). A towed magnetic gradiometer array for rapid, detailed imaging of utility, geological, and archaeological targets. Geoscientific Instrumentation, Methods and Data Systems, 10(2), 313-323. https://doi.org/10.5194/gi-10-313-2021

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