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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Mashhadi, S. R., Grombacher, D., Pedersen, J. B., Jørgensen, F., Andersen, T. R. & Griffiths, M. P. (2024). Estimation of hydraulic conductivity variations within glacial sediments at Endelave island by borehole NMR data. I 30th European Meeting of Environmental and Engineering Geophysics, Held at the Near Surface Geoscience Conference and Exhibition 2024, NSG 2024 European Association of Geoscientists and Engineers, EAGE. https://doi.org/10.3997/2214-4609.202420047

Todnem Bach Christensen, L., 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. I 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA (s. 1-4). IEEE. https://doi.org/10.1109/EMBC53108.2024.10781771

Sarabakha, A. & Suganthan, P. N. (2023). anafi_ros: from Off-the-Shelf Drones to Research Platforms. I 2023 International Conference on Unmanned Aircraft Systems (ICUAS) (s. 1308-1315) https://doi.org/10.1109/ICUAS57906.2023.10155881

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

So, P., Sarabakha, A., Wu, F., Culha, U., Abu-Dakka, F. & Haddadin, S. (2024). Digital Robot Judge: Building a Task-centric Performance Database of Real-World Manipulation With Electronic Task Boards. IEEE Robotics and Automation Magazine, 31(4), 32-44. https://doi.org/10.1109/MRA.2023.3336473

Qiao, Z., Pham, X. H., Ramasamy, S., Jiang, X., Kayacan, E. & Sarabakha, A. (2024). Continual Learning for Robust Gate Detection under Dynamic Lighting in Autonomous Drone Racing. I 2024 International Joint Conference on Neural Networks, IJCNN 2024 - Proceedings IEEE. https://doi.org/10.1109/ijcnn60899.2024.10649903

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

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 fra AGU Fall meeting 2024, Washington DC, USA.

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

Naveed, K. & Larsen, J. J. (2024). Variational Mode Decomposition Based Processing of Surface NMR Data. I 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. I NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (s. 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. I NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (s. 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. I NSG 2024 30th European Meeting of Environmental and Engineering Geophysics (s. 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. I NSG 2024 30th European Meeting of Environmental and Engineering Geophysics (s. 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. I NSG 2024 4th Conference on Airborne, Drone and Robotic Geophysics (s. 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. Afhandling præsenteret på 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. I NSG 2024 30th European Meeting of Environmental and Engineering Geophysics (s. 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 fra AGU Fall meeting 2024, Washington DC, USA.

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 fra AGU Fall meeting 2024, Washington DC, USA.

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

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. I 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. I 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, Artikel 1433234. https://doi.org/10.3389/fcogn.2024.1433234

Nazari, M., Korshoej, A. R. & Rehman, N. U. (2024). Graph-Aided Multivariate Signal Decomposition. I International Conference on Frontiers of Signal Processing (ICFSP) (s. 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), Artikel 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. (s. 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. 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

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), Artikel 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, Artikel 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), Artikel 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. I Book of Abstracts of the 75th Annual Meeting of the European Federation of Animal Science (s. 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. Afhandling præsenteret på 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. 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

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), Artikel 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, Artikel 109519. https://doi.org/10.1016/j.sigpro.2024.109519