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

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Christiansen, A. V. (2024). Extrapolating sparse SNMR data sets onto dense TEM coverage using spatially variable correlations. Abstract from AGU Fall meeting 2024, Washington DC, United States.

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.

Naveed, K. & Larsen, J. J. (2024). Variational Mode Decomposition Based Processing of Surface NMR Data. In NSG2024, 30th European Meeting of Environmental and Engineering Geophysics European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420100

Hardenberg, M., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2024). Feasibility study of steady-state surface NMR with adiabatic pulses. In NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420051

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Christiansen, A. V. (2024). Clustering on SNMR and TEM parameters over a saline-freshwater interface to resolve hydrogeological layers. In NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420102

Asif, MR., Larsen, JJ. & Christiansen, AV. (2024). Automated Processing of Time-Domain Electromagnetic Data Influenced by Induced Polarization Effects. In NSG 2024 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420140

Rafiei, M., Asif, MR., Nørremark, M. & Sørensen, CAG. (2024). High-Resolution Near-Surface Soil Water Content Estimation, Using Remote Sensing Data and Deep Computer Vision Methods. In NSG 2024 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420111

Millinge, O., Böttner, C. & Asif, MR. (2024). Deep Learning based Identification of Oil-Slick Emissions in the Arctic Using Satellite SAR Data. In NSG 2024 4th Conference on Airborne, Drone and Robotic Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420159

Griffiths, M. P. & Hardenberg, M. (2024). Feasibility study of steady-state surface NMR with adiabatic pulses. Paper presented at EAGE Near Surface Geoscience, Helsinki, Finland.

Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2024). Synthetic studies to investigate the ability of steady-state surface NMR to resolve T2. In NSG 2024 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420092

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

Grombacher, D., Griffiths, M. P. & Maurya, P. K. (2024). Estimation of transmitter-receiver separation for mobile ground-based transient electromagnetic systems using on-time gates. Abstract from AGU Fall meeting 2024, Washington DC, United States.

Griffiths, M. P., Grombacher, D., Mashhadi, S. R. & Larsen, J. J. (2024). Ground-truth Validation of T₂ Estimates from Steady-state Surface NMR. Abstract from AGU Fall meeting 2024, Washington DC, United States.

Asif, M. R., Kass, M. A., Herpe, M., Rawlinson, Z., Westerhoff, R., Larsen, J. J. & Christiansen, A. V. (2025). Comparative analysis of deep learning and traditional airborne electromagnetic data processing: A case study. Geophysics, 90(3), WA103-WA112. https://doi.org/10.1190/geo2024-0282.1

Vang, M., Grombacher, D., Larsen, J. J. & Wilson, S. (2023). SMALL COIL SURFACE NUCLEAR MAGNETIC RESONANCE FOR SHALLOW RESOLUTION OF RIVERS IN NEW ZEALAND. Proceedings of the Symposium on the Application of Geophyics to Engineering and Environmental Problems, SAGEEP, 2023-April.

Griffiths, M., Grombacher, D., Kass, M. A., Liu, L., Vang, M. & Larsen, J. J. (2022). A Reformulated Surface Nmr Forward For Multi-Sequence Acquisitions. In 28th European Meeting of Environmental and Engineering Geophysics, Held at the Near Surface Geoscience Conference and Exhibition 2022, NSG 2022 European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202220109

Vang, M., Grombacher, D., Larsen, J. J. & Wilson, S. (2023). Small coil surface nuclear magnetic resonance in dynamic river systems in New Zealand. In 2nd Conference on Hydrogeophysics 2023, Held at Near Surface Geoscience Conference and Exhibition 2023, NSG 2023 European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202320070

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

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

Morante Moreno, M., Frølich, K., Shahzaib, M., shakil, S. & Rehman, N. U. (2024). Multiscale Functional Connectivity analysis of episodic memory reconstruction. Frontiers in Cognition, 3, Article 1433234. https://doi.org/10.3389/fcogn.2024.1433234

Nazari, M., Korshoej, A. R. & Rehman, N. U. (2024). Graph-Aided Multivariate Signal Decomposition. In International Conference on Frontiers of Signal Processing (ICFSP) (pp. 169-173) https://doi.org/10.1109/ICFSP62546.2024.10785500

Griffiths, M. P., Grombacher, D., Mashhadi, S. R. & Larsen, J. J. (2024). Ground-Truth Validation of T₂ Estimates From Steady-State Surface NMR. Geophysical Research Letters, 51(24), Article e2024GL112094. https://doi.org/10.1029/2024GL112094

Christensen, L. T. B., Straadt, D., Vassis, S., Lillelund, C. M., Stoustrup, P. B., Pauwels, R., Pedersen, T. K. & Pedersen, C. F. (2024). An Explainable and Conformal AI Model to Detect Temporomandibular Joint Involvement in Children Suffering from Juvenile Idiopathic Arthritis. (pp. 1-4). https://arxiv.org/abs/2405.01617#

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. In A. Leonardis , E. Ricci , S. Roth , O. Russakovsky , T. Sattler & G. Varol (Eds.), Computer Vision – ECCV 2024 - 18th European Conference, Proceedings (pp. 55-73). Springer. https://doi.org/10.1007/978-3-031-72913-3_4

Naveed, K. & Rehman, N. U. (2025). Fully multivariate detrended fluctuation analysis using Mahalanobis norm with application to multivariate signal denoising. Measurement: Journal of the International Measurement Confederation, 242(Part E), Article 116142. https://doi.org/10.1016/j.measurement.2024.116142

Bjerge, K., Karstoft, H., Mann, H. M. R. & Høye, T. T. (2024). A deep learning pipeline for time-lapse camera monitoring of insects and their floral environments. Ecological Informatics, 84, Article 102861. https://doi.org/10.1016/j.ecoinf.2024.102861

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), Article e2024GL110826. https://doi.org/10.1029/2024GL110826

Sahana, G., Gebreyesus, G., Cheruiyot Bett , R., Kinyua, J., Roos, N., MBI Tanga, C., Mwikirize, C., Akol, R., Khamis, F. M., Karstoft, H., Bjerge, K., Nkirote Kunyanga , C., Hansen, L. S., Nielsen, H. M., Lund, M. S., Geoffrey, S., Walusimbi, S. & Nakimbugwe, D. (2024). FLYgene: Advancing Sustainable Breeding Programs and Genomic Tools for Black Soldier Fly (Hermetia illucens) in Kenya and Uganda. In Book of Abstracts of the 75th Annual Meeting of the European Federation of Animal Science (pp. 633-633) https://docs.eaap.org/boa/2024_Florence_EAAP_Book_Abstracts.pdf

Oleksiienko, I., Nousi, P., Passalis, N., Tefas, A. & Iosifidis, A. (2024). Vpit: real-time embedded single object 3D tracking using voxel pseudo images. Neural Computing and Applications, 36(32), 20341-20354. https://doi.org/10.1007/s00521-024-10259-2

Bjerge, K., Karstoft, H. & Høye, T. T. (2024). Towards edge processing of images from insect camera traps. bioRxiv. https://doi.org/10.1101/2024.07.01.601488

Bjerge, K., Karstoft, H., Mann, H. M. R. & Høye, T. T. (2024). A deep learning pipeline for time-lapse camera monitoring of floral environments and insect populations. bioRxiv. https://doi.org/10.1101/2024.04.12.589205

Bjerge, K., Bodesheim, P. & Karstoft, H. (2024). Few-Shot Learning with Novelty Detection. 340-363. Paper presented at DeLTA 2024 - 5th International Conference on Deep Learning Theory and Applications. https://doi.org/10.1007/978-3-031-66694-0_21

Lillelund, C. M., Magris, M. & Pedersen, C. F. (2025). Efficient Training of Probabilistic Neural Networks for Survival Analysis. IEEE Journal of Biomedical and Health Informatics, 29(9), 6157-6166. https://doi.org/10.1109/JBHI.2024.3417369

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

Roy, D. B., Alison, J., August, T. A., Bélisle, M., Bjerge, K., Bowden, J. J., Bunsen, M. J., Cunha, F., Geissmann, Q., Goldmann, K., Gomez-Segura, A., Jain, A., Huijbers, C., Larrivée, M., Lawson, J. L., Mann, H. M., Mazerolle, M. J., McFarland, K. P., Pasi, L. ... Høye, T. T. (2024). Towards a standardized framework for AI-assisted, image-based monitoring of nocturnal insects. Philosophical Transactions of the Royal Society B: Biological Sciences, 379(1904), Article 20230108. https://doi.org/10.1098/rstb.2023.0108

Nazari, M., Korshøj, A. R. & ur Rehman, N. (2024). Multiscale dynamic graph signal analysis. Signal Processing, 222, Article 109519. https://doi.org/10.1016/j.sigpro.2024.109519

Haldrup, M., Nazari, M., Gu, C., Rasmussen, M., Dyrskog, S., Ziegler Simonsen, C., Grønhøj, M., Poulsen, F. R., Ur Rehman, N. & Rosendal Korshoej, A. (2024). Reliability and performance of the IRRAflow® system for intracranial lavage and evacuation of hematomas-A technical note. PLoS One, 19(4 April), Article e0297131. https://doi.org/10.1371/journal.pone.0297131

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

D’Ambrosio, F., Harbo, M., Contiero, D., Bonfigli, A. R., Cicconi, D., Heuer, N., Roos, A., Pedersen, C. F., Fabbietti, P. & Gagliardi, C. (2024). Preact to lower the risk of falling by customized rehabilitation across Europe: the feasibility study protocol of the PRECISE project in Italy. Frontiers in Public Health, 12, Article 1293621. https://doi.org/10.3389/fpubh.2024.1293621

Nawoya, S., Geissmann, Q., Karstoft, H., Bjerge, K., Akol, R., Katumba, A., Mwikirize, C. & Gebreyesus, G. (2024). Computer-vision based prediction of body traits and larval sex in black soldier fly. Abstract from Insects for the Green Economy: Sustainable Food
Systems and Livelihoods in Africa, Nairobi, Kenya. https://qgg.au.dk/fileadmin/site_files/mb/QGG/Billeder/FLYgene/book-of-abstracts-insects-for-the-green-economy-conference-feb2024.pdf

Gebreyesus, G., Cheruiyot Bett , R., Nakimbugwe, D., Hansen, L. S., Nielsen, H. M., Karstoft, H., Bjerge, K., Nkirote Kunyanga , C., MBI Tanga, C., Mwikirize, C., Akol, R., Katumba, A., Khamis, F., Kinyua, J., Walusimbi, S., Geoffrey, S., Roos, N. & Sahana, G. (2024). Prospects of implementing black soldier fly (BSF) selective breeding in Kenya and Uganda: Status from the FlyGene Project. Abstract from Insects for the Green Economy: Sustainable Food
Systems and Livelihoods in Africa, Nairobi, Kenya. https://qgg.au.dk/fileadmin/site_files/mb/QGG/Billeder/FLYgene/book-of-abstracts-insects-for-the-green-economy-conference-feb2024.pdf

Grombacher, D., Griffiths, M. P., Kass, M. A. & Larsen, J. J. (2024). An investigation of factors affecting the depths of steady-state surface nuclear magnetic resonance signals. Geophysics, 89(2), J9-J17. https://doi.org/10.1190/geo2023-0068.1

Nazari, M., Korshoej, A. R. & Rehman, N. U. (2024). Multiscale Dynamic Graph Signal Analysis. Social Science Research Network (SSRN). https://doi.org/10.2139/ssrn.4713829

Oleksiienko, I., Tran, D. T. & Iosifidis, A. (2023). Variational Neural Networks. Procedia Computer Science, 222, 104-113. https://doi.org/10.1016/j.procs.2023.08.148

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

Oleksiienko, I., Nousi, P., Passalis, N., Tefas, A. & Iosifidis, A. (2023). Variational Voxel Pseudo Image Tracking. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 323-328). IEEE. https://doi.org/10.1109/SSCI52147.2023.10371810

Naveed, K., Madsen, L. M., Grombacher, D. & Larsen, J. J. (2024). Processing Time-domain Induced Polarization Data Using Variational Mode Decomposition. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-13. Article 5905713. https://doi.org/10.1109/TGRS.2024.3362290

Amer, A. H. K. S. A., Mehndiratta, M., Sejersen, J. L. F., Pham, X. H. & Kayacan, E. (2024). Visual Tracking Nonlinear Model Predictive Control Method for Autonomous Wind Turbine Inspection. In 2023 21st International Conference on Advanced Robotics (ICAR) (pp. 431-438). IEEE. https://doi.org/10.1109/ICAR58858.2023.10406329

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

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