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Department of Electrical and Computer Engineering

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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Salavatidezfouli, S., Rakhsha, S., Sheidani, A., Stabile, G. & Rozza, G. (2025). A predictive surrogate model for heat transfer of an impinging jet on a concave surface. International Journal of Heat and Mass Transfer, 251, Article 127248. https://doi.org/10.1016/j.ijheatmasstransfer.2025.127248

Rafiei Foroushani, M. (2024). Advancing Computer Vision in Irregular Texture Product Analysis. Aarhus University.

Pedersen, C. F. (2012). Z-transform Zeros in Mixed Phase Deconvolution of Speech. Aalborg University, Faculty of Engineering and Science, Dept. of Electronic Systems, Niels Jernes Vej 10, 9220 Aalborg East, Denmark.

Skovsen, S. K. (2021). Mixed Crop Mapping by Species Discrimination using Data Driven Computer Vision and Simulated Data. Århus Universitet.

Pham, X. H. (2023). Efficient deep learning-based monocular 3D perception for agile robot navigation. Århus Universitet.

Oleksiienko, I. (2023). Uncertainty Estimation for 3D Object Detection and Tracking. Aarhus University.

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

Asif, M. R. (2025). Benchmarking Deep Learning for Wetland Mapping in Denmark Using Remote Sensing Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 18, 11953-11962. https://doi.org/10.1109/JSTARS.2025.3563951

Safari, A., Saidi, M. H., Salavatidezfouli, S., Ma, W. & Yao, S. (2025). A comprehensive experimental and numerical study of Taylor-Couette flow on superhydrophobic surfaces. AIP Advances, 15(5), Article 055012. https://doi.org/10.1063/5.0249290

D'Inverno, G. A., Moradizadeh, S., Salavatidezfouli, S., Africa, P. C. & Rozza, G. (2025). Mesh-informed Reduced Order Models for aneurysm rupture risk prediction. Journal of Computational and Applied Mathematics, 470, Article 116727. https://doi.org/10.1016/j.cam.2025.116727

Ong, S.-Q., Pinoy, N., Hui Lin, M., Bjerge, K., Peris-Felipo, F. J., Lind, R., P. Cuff, J., M. Cook, S. & Høye, T. T. (2025). ScannerVision: Scanner-based image acquisition of medically important arthropods for the development of computer vision and deep learning models. Current Research in Parasitology & Vector-Borne Diseases, 7, Article 100268. https://doi.org/10.1016/j.crpvbd.2025.100268

Nawoya, S., Geissmann, Q., Karstoft, H., Bjerge, K., Akol, R., Katumba, A., Mwikirize, C. & Gebreyesus, G. (2025). Prediction of black soldier fly larval sex and morphological traits using computer vision and deep learning. Smart Agricultural Technology, 11, Article 100953. https://doi.org/10.1016/j.atech.2025.100953

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Wilson, S. (2025). Efficient mapping of complex groundwater systems associated with braided rivers using small coil surface nuclear magnetic resonance. Geophysics, 90(3), 1-12. https://doi.org/10.1190/geo2023-0765.1

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

Barzegar Gerdroodbary, M. & Salavatidezfouli, S. (2025). A predictive surrogate model of blood haemodynamics for patient-specific carotid artery stenosis. Journal of the Royal Society Interface, 22(224), Article 20240774. https://doi.org/10.1098/rsif.2024.0774

Barzegar Gerdroodbary, M. & Salavatidezfouli, S. (2025). A predictive surrogate model based on linear and nonlinear solution manifold reduction in cardiovascular FSI: A comparative study. Computers in Biology and Medicine, 189, Article 109959. https://doi.org/10.1016/j.compbiomed.2025.109959

Liang, W., Amer, A., Mehndiratta, M., Chen, Z., Yao, B. & Kayacan, E. (2025). Adaptive Robust Control Integrated With Gaussian Processes for Quadrotors: Enhanced Accuracy, Fault Tolerance and Anti-Disturbance. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 55(5), 3235-3248. https://doi.org/10.1109/TSMC.2025.3539707

Amer, A. H. K. S. A., Alvarez Tunon, O., Ugurlu, H. I., Sejersen, J. L. F., Brodskiy, Y. & Kayacan, E. (2024). UNav-Sim: A Visually Realistic Underwater Robotics Simulator and Synthetic Data-Generation Framework. In 2023 21st International Conference on Advanced Robotics (ICAR) https://ieeexplore.ieee.org/abstract/document/10406819

Sejersen, J. L. F. & Kayacan, E. (2023). CAMETA: Conflict-Aware Multi-Agent Estimated Time of Arrival Prediction for Mobile Robots. 1-8. Paper presented at 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Detroit, Michigan, United States. https://doi.org/10.1109/IROS55552.2023.10341937

Sejersen, J. L. F., Sarabakha, A., Plagborg Bak Sørensen, K. & Høigaard Jensen, J. (2025). Multi-Agent Path Planning in Complex Environments using Gaussian Belief Propagation with Global Path Finding. 1-7. Paper presented at 2025 IEEE International Conference on Robotics and Automation (ICRA) , Atlanta, Georgia, United States. https://arxiv.org/abs/2502.20369

Liu, L., Domenzain Gonzalez, D., Vela, I., Maurya, P. K., Kühl, A. K., Bording, T., Ejlskov, P., Auken, E., Larsen, J. J. & Christiansen, A. V. (2025). An efficient cross-borehole direct current resistivity monitoring instrument. Geophysics, 90(2), D61-D70. https://doi.org/10.1190/geo2023-0518.1

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

Bjerge, K., Bodesheim, P. & Karstoft, H. (2025). Deep Image Clustering with Model-Agnostic Meta-Learning. In In Proceedings of the 20th International Joint Conference on Computer Vision (Vol. 2, pp. 286-297). Imaging and Computer Graphics Theory and Applications - VISAPP 2025. https://doi.org/10.5220/0013114600003912

Naveed, K. & Ur Rehman, N. (2024). Variational Mode Decomposition Denoising Using Anderson-Darling Statistics. In 2024 9th International Conference on Frontiers of Signal Processing, ICFSP 2024 (pp. 189-193). IEEE. https://doi.org/10.1109/ICFSP62546.2024.10785266

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

Dobbs, A. M., Goldsmith, A. S., Ginn, D., Skovsen, S. K., Bagavathiannan, M. V., Mirsky, S. B., Reberg-Horton, C. S. & Leon, R. G. (2024). Mapping predicted biomass in cereal rye using 3D imaging and geostatistics. Weed Science, 72(5), 553-561. https://doi.org/10.1017/wsc.2024.62

Sarabakha, A. & Suganthan, P. N. (2023). anafi_ros: from Off-the-Shelf Drones to Research Platforms. In 2023 International Conference on Unmanned Aircraft Systems (ICUAS) (pp. 1308-1315)

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://ieeexplore.ieee.org/document/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. Robotics Automation Magazine, IEEE.

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. In 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. 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

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AU Engineering