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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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.

Pedersen, C. F. (2011). Leja ordering LSFs for accurate estimation of predictor coefficients. Proceedings of the International Conference on Spoken Language Processing.

Jørgensen, R. N. (2011). Leg med store perspektiver. Land&Liv, 2011(uge 25), 13. http://www.e-pages.dk/landogliv/5/13

Bozorgtabar, B., Rad, M. S., Ekenel, H. K. & Thiran, J.-P. (2019). Learn to synthesize and synthesize to learn.

Anklin, V., Pati, P., Jaume, G., Bozorgtabar, B., Foncubierta-Rodríguez, A., Thiran, J.-P., Sibony, M., Gabrani, M. & Goksel, O. (2021). Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs.

Oleksiienko, I. & Iosifidis, A. (2023). Layer Ensembles. I D. Comminiello & M. Scarpiniti (red.), 2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP) IEEE. https://doi.org/10.1109/MLSP55844.2023.10286005

Beevi, F. H. A., Pedersen, C. F., Wagner, S. R. & Hallerstede, S. (2014). Lateral Fall Detection via Events in Linear Prediction Residual of Acceleration. I C. Ramos, P. Novais, C. Ehrwein Nihan & J. M. Corchado Rodriguez (red.), Ambient Intelligence - Software and Applications: 5th International Symposium on Ambient Intelligence (Bind 291, s. 201-208). Springer. https://doi.org/10.1007/978-3-319-07596-9_22

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

Rathish, H., Picón, G. C. & Schulz, H.-J. (2024). LaNe Plot: A Visual Fingerprinting Technique for Sequential Data. I K. Kucher, A. Diehl & C. Gillmann (red.), Poster Proceedings of the 26th Eurographics Conference on Visualization The Eurographics Association. https://doi.org/10.2312/evp.20241087

Pedersen, C. F., Trier Lund, M., Vardinghus Nielsen, C., Fromberg, J., Sloth, S., Bay Velling, M., Staach, L. & Lorenzen, T. (2000). Læring med IT: Novo Nordisk Projektet. Billeder, Video- og Lydoptagelser (digital), Novo Nordisk and The Danish Ministry of Education.

Karstoft, H. (2010). Kursus i Wavelets for ingeniører: Noter til Tisib2. Ingeniørhøjskolen i Aarhus.

Jørgensen, R. & Hansen, P. M. (2000). Kunstigt øje vogter over planters ernæringstilstand. Risoenyt, 2, 12-13.

Green, O. & Jørgensen, R. (2007). Kørselsskader i græs. Poster-session præsenteret på Temadag på Institut for Jordbrugsteknik - et vindue til fremtidens markteknologi, Horsens.

Zhou, S., Helwa, M. K., Schoellig, A. P., Sarabakha, A. & Kayacan, E. (2019). Knowledge transfer between robots with similar dynamics for high-accuracy impromptu trajectory tracking. I 2019 18th European Control Conference, ECC 2019 Artikel 8796140 IEEE. https://doi.org/10.23919/ECC.2019.8796140

Høye, T. T., Mann, H. M. R. & Bjerge, K. (2020). Kamerabaseret overvågning af Insekter på grønne bytage. Aarhus University, DCE - Danish Centre for Environment and Energy. Videnskabelig rapport fra DCE - Nationalt Center for Miljø og Energi Nr. 371 https://dce2.au.dk/pub/SR371.pdf

Nazari, M., Korshøj, A. R. & Rehman, N. U. (2024). Jump Plus AM-FM Mode Decomposition. Cornell University. https://doi.org/10.48550/arXiv.2407.07800

Nazari, M., Korshj, A. R. & Rehman, N. U. (2025). Jump Plus AM-FM Mode Decomposition. IEEE Transactions on Signal Processing, 73, 1081-1093. https://doi.org/10.1109/TSP.2025.3535822

Liu, L., Griffiths, M. P., Vang, M., Grombacher, D. J. & Larsen, J. J. (2021). Is it redundant to use model-based subtraction together with the reference noise cancellation? I 27th European Meeting of Environmental and Engineering Geophysics, Held at Near Surface Geoscience Conference and Exhibition 2021, NSG 2021 EAGE Publishing BV. https://doi.org/10.3997/2214-4609.202120108

Nielsen, A. H., Iosifidis, A. & Karstoft, H. (2021). IrradianceNet: Spatiotemporal Deep Learning Model for Satellite-Derived Solar Irradiance Nowcasting. Solar Energy, 228, 659-669. https://doi.org/10.1016/j.solener.2021.09.073

Rafiei Foroushani, M. & Nørremark, M. (2025). Investigation of available ground-truth data in Denmark that can be used for remote identification and localization of populations of selected plant species. DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug

Gentili, M., Tanaka, T., Nichols, V. A., Jørgensen, R. N., Jørgensen, J. R. & Gislum, R. (2025). Investigating weed and companion plant ecosystem services and disservices distribution maps using machine learning: Joint approaches for sustainable weed management. I 20TH EUROPEAN WEED RESEARCH SOCIETY SYMPOSIUM: Joint Approaches for Sustainable Weed Management (s. 340-340). European Weed Research Society. https://doi.org/10.21001/20.weed.research.society.symposium.2025

Asif, M. R., Maurya, P. K., Larsen, J. J. & Christiansen, A. V. (2022). Investigating the Integration of Neural Networks in Least-Squares Method for Airborne Electromagnetic Data Inversion. 1-5. Afhandling præsenteret på NSG2022 3rd Conference on Airborne, Drone and Robotic Geophysics, Beograd, Serbien. https://doi.org/10.3997/2214-4609.202220034

Grombacher, D., Liu, L., Kass, M. A., Osterman, G., Fiandaca, G., Auken, E. & Larsen, J. J. (2020). Inverting surface NMR free induction decay data in a voltage-time data space. Journal of Applied Geophysics, 172, Artikel 103869. https://doi.org/10.1016/j.jappgeo.2019.103869

Sarabakha, A., Fu, C. & Kayacan, E. (2019). Intuit before tuning: Type-1 and type-2 fuzzy logic controllers. Applied Soft Computing Journal, 81, Artikel 105495. https://doi.org/10.1016/j.asoc.2019.105495

Haldrup, M., Rasmussen, M., Mohamad, N., Dyrskog, S., Thorup, L., Mikic, N., Wismann, J., Grønhøj, M., Poulsen, F. R., Nazari, M., Rehman, N. U., Simonsen, C. Z. & Korshøj, A. R. (2023). Intraventricular Lavage vs External Ventricular Drainage for Intraventricular Hemorrhage: A Randomized Clinical Trial. JAMA network open, 6(10), e2335247. Artikel e2335247. https://doi.org/10.1001/jamanetworkopen.2023.35247

Jensen, T. & Karstoft, H. (2014). Intelligent Soil Tillage. Abstract fra AGROMEK and NJF Joint Seminar on Future Arable Farming and Agricultural Engineering, Herning, Danmark.

Asif, M. R., Foged, N., Maurya, P. K., Grombacher, D. J., Christiansen, A. V., Auken, E. & Larsen, J. J. (2022). Integrating neural networks in least-squares inversion of airborne time-domain electromagnetic data. Geophysics, 87(4), E177-E187. https://doi.org/10.1190/geo2021-0335.1

Ehsan, S., Clark, A., Rehman, N. & McDonald-Maier, K. (2015). Integral Images: Efficient Algorithms for Their Computation and Storage in Resource-Constrained Embedded Vision Systems. Sensors, 15(7), 16804-16830. https://doi.org/10.3390/s150716804

Jain, A., Cunha, F., Bunsen, M. J., Cañas, J. S., Pasi, L., Pinoy, N., Helsing, F., Russo, J., Botham, M., Sabourin, M., Fréchette, J., Anctil, A., Lopez, Y., Navarro, E., Perez Pimentel, F., Zamora, A. C., Silva, J. A. R., Gagnon, J., August, T. ... Rolnick, D. (2025). Insect Identification in the Wild: The AMI Dataset. I A. Leonardis , E. Ricci , S. Roth , O. Russakovsky , T. Sattler & G. Varol (red.), Computer Vision – ECCV 2024 - 18th European Conference, Proceedings (s. 55-73). Springer. https://doi.org/10.1007/978-3-031-72913-3_4

Fu, C., Sarabakha, A., Kayacan, E., Wagner, C., John, R. & Garibaldi, J. M. (2018). Input Uncertainty Sensitivity Enhanced Non-Singleton Fuzzy Logic Controllers for Long-Term Navigation of Quadrotor VTOL UAVs. IEEE - ASME Transactions on Mechatronics, 23(2), 725-734. https://doi.org/10.1109/TMECH.2018.2810947

Gebreyesus, G., Nawoya, S., Ssemakula, F., Karstoft, H., Bjerge, K., Kunyanga, C. N., Mwikirize, C., Akol, R., Katumba, A., Nakimbugwe, D. & Geissmann, Q. (2024). Innovative phenotyping systems to advance selective breeding in black soldier fly: status from the FlyGene project. Journal of Insects as Food and Feed, 10(Supplement 1 (2024) S1–S353), S250. Artikel Volume 10, Supplement 1 (2024). https://doi.org/10.1163/23524588-20241013

Jain, S., Naveed, K., Oleksiienko, I., Iosifidis, A. & Pauwels, R. (2025). InJecteD: Analyzing Trajectories and Drift Dynamics in Denoising Diffusion Probabilistic Models for 2D Point Cloud Generation. CEUR Workshop Proceedings, 4072, 91-99.

Farkhani, S., Skovsen, S. K., Mortensen, A. K., Laursen, M. S., Nyholm Jørgensen, R. & Karstoft, H. (2020). Initial evaluation of enriching satellite imagery using sparse proximal sensing in precision farming. I C. M. U. Neale & A. Maltese (red.), Remote Sensing for Agriculture, Ecosystems, and Hydrology XXII (Bind 11528). Artikel 115280A SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2573626

Nyord, T., Steen, K. A. & Nyholm Jørgensen, R. (2014). Infrared measurements used as soil infiltration indicator for animal slurry. I International Conference of Agricultural Engineering - AgEng 2014 Zurich The European Society of Agricultural Engineers (EurAgEng). http://www.geyseco.es/ageng2014/eposter/?seccion=posters&idcomunicacion=556&tipo=3

Bozorgtabar, B., Mahapatra, D., von Teng, H., Pollinger, A., Ebner, L., Thiran, J.-P. & Reyes, M. (2019). Informative sample generation using class aware generative adversarial networks for classification of chest Xrays.

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

Midtiby, H., Mosgaard Giselsson, T. & Jørgensen, R. N. (2010). Independent feature based plant classification.

Laursen, M. S., Nyholm Jørgensen, R. & Midtiby, H. S. (2014). Improving the segmentation for weed recognition applications based on standard RGB cameras using optical filters. Abstract fra Agromek and NJF joint seminar, Herning, Danmark.

Vassis, S., Todnem, L., Straadt, D., Pedersen, C. F., Noeldeke, B., Resnick, C. M., Glerup, M., Pedersen, T. K., Pauwels, R. & Stoustrup, P. (2025). Improving early detection of temporomandibular joint involvement in juvenile idiopathic arthritis with a clinically interpretable machine learning model. Scientific Reports, 15(1), Artikel 39120. https://doi.org/10.1038/s41598-025-25988-0

Asif, M. R., Bording, T. S., Barfod, A. A. S., Zhang, B., Larsen, J. J. & Auken, E. (2020). Improving computational efficiency of forward modelling for ground-based time-domain electromagnetic data using neural networks. Abstract fra EGU:General assembly 2020 , Vienna , Østrig. https://doi.org/10.5194/egusphere-egu2020-7067

Chavez Plascencia, A. & Karstoft, H. (2012). Improvement of KinectTM Sensor Capabilities by Fusion with Laser Sensing Data Using Octree. Sensors, 12, 3868-3878. https://doi.org/10.3390/s120403868

Liu, L., Grombacher, D. J., Auken, E. & Larsen, J. J. (2018). Improved parameters estimates for surface-NMR data using spectral analysis. Afhandling præsenteret på 7th International Workshop on Magnetic Resonance, Jilin, Kina.

Nielsen, S. H., Bøgild, A., Jensen, K., Kjærhus Bertelsen, K. & Jørgensen, R. N. (2011). Implementations of FroboMind using the Robot Operating System framework. http://www.njf.nu/site/seminarRedirect.asp?intSeminarID=441&p=1004

Ma, X., J. Hegarty, P., Abildgaard Pedersen, J. & Larsen, J. J. (2018). Impact of loudspeaker nonlinear distortion on personal sound zones. Acoustical Society of America. Journal, 143(51), 51-59. https://doi.org/10.1121/1.5019476

Rubak, J. A. B., Naveed, K., Jain, S., Esterle, L., Iosifidis, A. & Pauwels, R. (2025). Impact of Labeling Inaccuracy and Image Noise on Tooth Segmentation in Panoramic Radiographs using Federated, Centralized and Local Learning. ArXiv. https://doi.org/10.48550/arXiv.2509.06553

Jaume, G., Bozorgtabar, B., Ekenel, H. K., Thiran, J.-P. & Gabrani, M. (2018). Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks.

Morales, T., Sarabakha, A. & Kayacan, E. (2020). Image Generation for Efficient Neural Network Training in Autonomous Drone Racing. I 2020 International Joint Conference on Neural Networks (IJCNN) Artikel 9206943 IEEE. https://doi.org/10.1109/IJCNN48605.2020.9206943

Rehman, N., Khan, M. M., Sohaib, M. I., Jehanzaib, M., Ehsan, S. & McDonald-Maier, K. (2014). Image fusion using multivariate and multidimensional EMD. I 2014 IEEE International Conference on Image Processing (ICIP) IEEE. https://doi.org/10.1109/icip.2014.7026035

Tu, G. J., Karstoft, H., Pedersen, L. J. & Jørgensen, E. (2015). Illumination and Reflectance Estimation with its Application in Foreground Detection. Sensors, 15(9), 21407-21426. https://doi.org/10.3390/s150921407

Asif, M. R., Kass, A., Larsen, J. J. & Christiansen, A. V. (2025). Identifying Induced Polarization Effects in TEM Data by Deep Learning. I 7th Asia Pacific Meeting on Near Surface Geoscience and Engineering, NSGE 2025 (s. 1-5). European Association of Geoscientists and Engineers, EAGE. https://doi.org/10.3997/2214-4609.202572056

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Revideret 13.11.2025

AU Engineering