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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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. (2024). 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 (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

Frasheri, M., Katsaros, P., Iosifidis, A., Hansen, S. T., Gomes, C., Evans, V. T. & Larsen, P. G. (2024). System Monitoring through a Digital Twin. In J. Fitzgerald, C. Gomes & P. G. Larsen (Eds.), The Engineering of Digital Twins (pp. 189-207). Springer. https://doi.org/10.1007/978-3-031-66719-0_9

Gomes, C., Lucani Rötter, D. E., Iosifidis, A., Feng, H., Ejersbo, H. & Frasheri, M. (2024). Sensing and Communication of Data from the Physical Twin. In J. Fitzgerald, C. Gomes & P. G. Larsen (Eds.), The Engineering of Digital Twins (pp. 147-171). Springer. https://doi.org/10.1007/978-3-031-66719-0_7#citeas

Magris, M., Shabani, M. & Iosifidis, A. (2024). Manifold Gaussian Variational Bayes on the Precision Matrix. Neural Computation, 36(9), 1744-1798. https://doi.org/10.1162/neco_a_01686

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. Paper presented at DeLTA 2024 - 5th International Conference on Deep Learning Theory and Applications.

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2024). ACCURATE GIGAPIXEL CROWD COUNTING BY ITERATIVE ZOOMING AND REFINEMENT. In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 6510-6514). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP48485.2024.10446065

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

Angelov, P., Bernardi, M. L., Nardini, F. M., Pecori, R., Valerio, L., Dini, P., Ashraf, S., Aversano, L., Bianchini, M., Brutti, A., Bukovsky, I., Cagnoni, S., Cao, J., Cimitile, M., Dazzi, P., Iammarino, M., Iosifidis, A., Michahelles, F., Mora, A. ... Welsh, M. (2024). PerconAI 2024: 3rd Workshop on Pervasive and Resource-Constrained Artificial Intelligence - Welcome and Committees. In 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (pp. 34-35). IEEE. https://doi.org/10.1109/PerComWorkshops59983.2024.10503466

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

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2024). Efficient High-Resolution Deep Learning: A Survey. ACM Computing Surveys, 56(7), 1 - 35. Article 181. https://doi.org/10.1145/3645107

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

Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2024). Reducing redundancy in the bottleneck representation of autoencoders. Pattern Recognition Letters, 178, 202-208. https://doi.org/10.1016/j.patrec.2024.01.013

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

Minh Nguyen, Q., Tran, D. T., Kanniainen, J., Iosifidis, A. & Gabbouj, M. (2024). Cryptocurrency Portfolio Optimization by Neural Networks. In 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 25-32). IEEE. https://doi.org/10.1109/SSCI52147.2023.10371855

Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2023). Learning Distinct Features Helps, Provably. In D. Koutra, C. Plant, M. Gomez Rodriguez, E. Baralis & F. Bonchi (Eds.), Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part II (pp. 206-222). Springer. https://doi.org/10.1007/978-3-031-43415-0_13

Wewer, C. R. & Iosifidis, A. (2023). Improving Online non-destructive Moisture Content Estimation using Data Augmentation by Feature Space Interpolation with Variational Autoencoders. In 2023 IEEE 21st International Conference on Industrial Informatics (INDIN) IEEE. https://doi.org/10.1109/INDIN51400.2023.10218063

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

Alvarez Tunon, O., Brodskiy, Y. & Kayacan, E. (2024). Monocular visual simultaneous localization and mapping:(r) evolution from geometry to deep learning-based pipelines. IEEE Transactions on Artificial Intelligence, 5(5), 1990-2010. Article 3321032. https://doi.org/10.1109/TAI.2023.3321032

Pham, X. H., Heiß, M., Tran, D., Nguyen, M. A., Nguyen, A. Q. & Kayacan, E. (2023). ORB-Net: End-to-end Planning Using Feature-based Imitation Learning for Autonomous Drone Racing. In ISR Europe 2023: 56th International Symposium on Robotics, in cooperation with Fraunhofer IPA September 26 – 27, 2023 in Stuttgart (pp. 16-21). VDE Verlag GmbH. https://ieeexplore.ieee.org/document/10363048

Alvarez Tunon, O., Kanner, H., Ribeiro Marnet, L., Pham, X. H., Sejersen, J. L. F., Brodskiy, Y. & Kayacan, E. (2023). MIMIR-UW: A Multipurpose Synthetic Dataset for Underwater Navigation and Inspection. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 6141-6148). IEEE. https://doi.org/10.1109/IROS55552.2023.10341436

Cavagna, A., Li, N., Iosifidis, A. & Zhang, Q. (2023). Semantic Communication Enabling Robust Edge Intelligence for Time-Critical IoT Applications. In 2023 IEEE International Conference on Communications Workshops (ICC Workshops) (pp. 1617-1622). IEEE. https://doi.org/10.1109/ICCWorkshops57953.2023.10283786

Li, N., Iosifidis, A. & Zhang, Q. (2023). Attention-Based Feature Compression for CNN Inference Offloading in Edge Computing. In M. Zorzi, M. Tao & W. Saad (Eds.), ICC 2023 - IEEE International Conference on Communications (pp. 967-972). IEEE. https://doi.org/10.1109/ICC45041.2023.10279110

Pauwels, R. & Iosifidis, A. (2024). Deep Learning in Image Processing: Part 2—Image Enhancement, Reconstruction and Registration. In K. Orhan & R. Jagtap (Eds.), Artificial Intelligence in Dentistry (pp. 317-351). Springer. https://doi.org/10.1007/978-3-031-43827-1_18

Pauwels, R. & Iosifidis, A. (2024). Deep Learning in Image Processing: Part 1—Types of Neural Networks, Image Segmentation. In Artificial Intelligence in Dentistry (pp. 283-316). Springer. https://doi.org/10.1007/978-3-031-43827-1_17

Asif, M. R., Kass, A., Westerhoff, R., Rawlinson, Z. & Christiansen, A. V. (2023). Automated data processing of a large-scale airborne time-domain electromagnetic survey by a deep learning expert system. Paper presented at 8th International Workshop on Airborne Electromagnetics, Queensland, Australia.

Asif, M. R., Kass, A., Westerhoff, R., Rawlinson, Z., Christiansen, A. V. & Bording, T. S. (2023). Automated Processing of a Large-Scale Airborne Electromagnetic Survey by Deep Learning. Paper presented at NSG2023 29th European Meeting of Environmental and Engineering Geophysics, Edinburgh , United Kingdom. https://doi.org/10.3997/2214-4609.202320057

He, S., Cai, H., Christiansen, A. V. & Asif, M. R. (2023). A Novel Normalization Method of Transient Electromagnetic Data for Efficient Neural Network Training. Paper presented at NSG2023 29th European Meeting of Environmental and Engineering Geophysics, Edinburgh , United Kingdom. https://doi.org/10.3997/2214-4609.202320125

Meldgaard Madsen, L., Asif, M. R., Maurya, P. K., Kühl, A. K., Domenzain, D., Jensen, C., Martin, T., Bastani, M. & Persson, L. (2023). Comparison of tTEM-IP and ERT-IP: Cases from Mine Tailing Sites in Sweden. Abstract from NSG2023 29th European Meeting of Environmental and Engineering Geophysics, Edinburgh , United Kingdom. https://doi.org/10.3997/2214-4609.202320114

Naveed, K., Meldgaard Madsen, L., Grombacher, D. & Larsen, J. J. (2023). Variational Mode Decomposition-Based Processing of Time-Domain Induced Polarization Data. Abstract from NSG2023 29th European Meeting of Environmental and Engineering Geophysics, Edinburgh , United Kingdom. https://doi.org/10.3997/2214-4609.202320133

Magris, M. & Iosifidis, A. (2023). Variational Inference for GARCH-family Models. In ICAIF 2023 - 4th ACM International Conference on AI in Finance (pp. 541-548). Association for Computing Machinery, Inc.. https://doi.org/10.1145/3604237.3626863

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Revised 10.08.2023

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