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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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

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

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

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

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

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.

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, Artikel 1293621. https://doi.org/10.3389/fpubh.2024.1293621

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. Artikel 5905713. https://doi.org/10.1109/TGRS.2024.3362290

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 fra 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

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), Artikel e0297131. https://doi.org/10.1371/journal.pone.0297131

Stegmüller, T., Abbet, C., Bozorgtabar, B., Clarke, H., Petignat, P., Vassilakos, P. & Thiran, J. P. (2024). Self-supervised learning-based cervical cytology for the triage of HPV-positive women in resource-limited settings and low-data regime. Computers in Biology and Medicine, 169, Artikel 107809. https://doi.org/10.1016/j.compbiomed.2023.107809

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.

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

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

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

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. I 2023 21st International Conference on Advanced Robotics (ICAR) https://ieeexplore.ieee.org/abstract/document/10406819

Tomar, D., Vray, G., Thiran, J. P. & Bozorgtabar, B. (2024). UN-MIXING TEST-TIME NORMALIZATION STATISTICS: COMBATTING LABEL TEMPORAL CORRELATION. Afhandling præsenteret på 12th International Conference on Learning Representations, ICLR 2024, Hybrid, Vienna, Østrig.

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

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

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. I 2023 21st International Conference on Advanced Robotics (ICAR) (s. 431-438). IEEE. https://doi.org/10.1109/ICAR58858.2023.10406329

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., Alison, J., Dyrmann, M., Frigaard, C. E., Mann, H. M. R. & Høye, T. T. (2023). Accurate detection and identification of insects from camera trap images with deep learning. PLOS Sustainability and Transformation, 2(3), Artikel e0000051. https://doi.org/10.1371/journal.pstr.0000051

Lebailly, T., Stegmüller, T., Bozorgtabar, B., Thiran, J.-P. & Tuytelaars, T. (2023). Adaptive Similarity Bootstrapping for Self-Distillation based Representation Learning. (s. 16459-16468). https://doi.org/10.1109/ICCV51070.2023.01513

Asif, M. R., Maurya, P. K., Foged, N. & Christiansen, A. V. (2023). A DATA DRIVEN APPROACH FOR ROBUST INVERSION OF INDUCED POLARIZATION EFFECTS IN TRANSIENT ELECTROMAGNETIC DATA. I APPLICATION OF GEOPHYSICS TO ENGINEERING AND ENVIRONMENTAL PROBLEMS: SYMPOSIUM. 35TH 2023. (SAGEEP 2023) (s. 82-82). Curran Associates.

Gaikwad, N., Liu, L., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2023). A High Duty Cycle Transmitter Unit for Steady-State Surface NMR Instruments. (s. 1-22). Geoscientific Instrumentation, Methods and Data Systems https://doi.org/10.5194/gi-2023-5

Bozorgtabar, B., Mahapatra, D. & Thiran, J.-P. (2023). Amae: Adaptation of Pre-Trained Masked Autoencoder for Dual-Distribution Anomaly Detection in Chest X-Rays.

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

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

Griffiths, M. P., Grombacher, D., Kass, M. A., Vang, M., Liu, L. & Larsen, J. J. (2023). A surface NMR forward in a dot product. Geophysical Journal International, 234(3), 2284-2290. https://doi.org/10.1093/gji/ggad203

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. Afhandling præsenteret på 8th International Workshop on Airborne Electromagnetics, Queensland, Australien.

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. Afhandling præsenteret på NSG2023 29th European Meeting of Environmental and Engineering Geophysics, Edinburgh , Storbritannien. https://doi.org/10.3997/2214-4609.202320057

Gislum, R., Larsen, R., Thomsen, I. K., Greve, M. B., Hansen, E. M. & Nyholm Jørgensen, R., (2023). Betingelse for indsamling af data til brug for omregningsfaktor mellem NDV/NDRE og planteoptag af kvælstof, Nr. 2023-0543874, 8 s., aug. 23, 2023. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Rafiei Foroushani, M. & Iosifidis, A. (2023). Class-Specific Variational Auto-Encoder for Content-Based Image Retrieval. I 2023 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN54540.2023.10191068

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 fra NSG2023 29th European Meeting of Environmental and Engineering Geophysics, Edinburgh , Storbritannien. https://doi.org/10.3997/2214-4609.202320114

Agerskov, J., Nielsen, K. & Pedersen, C. F. (2023). Computationally Efficient Labeling of Cancer-Related Forum Posts by Non-Clinical Text Information Retrieval. SN Computer Science, 4(6), Artikel 711. https://doi.org/10.1007/s42979-023-02244-8

Rafiei Foroushani, M., Raitoharju, J. & Iosifidis, A. (2023). Computer Vision on X-Ray Data in Industrial Production and Security Applications: A Comprehensive Survey. IEEE Access, 11, 2445 - 2477. https://doi.org/10.1109/ACCESS.2023.3234187

Stegmüller, T., Lebailly, T., Bozorgtabar, B., Tuytelaars, T. & Thiran, J.-P. (2023). CrOC: Cross-View Online Clustering for Dense Visual Representation Learning.

Eriksen, T. & Rehman, N. U. (2023). Data-driven nonstationary signal decomposition approaches: a comparative analysis. Scientific Reports, 13(1), Artikel 1798. https://doi.org/10.1038/s41598-023-28390-w

Jakobsen, M. O., Herskind, E. S., Pedersen, C. F. & Knudsen, M. B. (2023). Detecting insufficient lubrication in rolling bearings, using a low cost MEMS microphone to measure vibrations. Mechanical Systems and Signal Processing, 200, Artikel 110553. https://doi.org/10.1016/j.ymssp.2023.110553

Asif, M. R., Foged, N., Bording, T. S., Larsen, J. J. & Christiansen, A. V. (2023). DL-RMD: a geophysically constrained electromagnetic resistivity model database for deep learning applications. Earth System Science Data, 15(3), 1389-1401. https://doi.org/10.5194/essd-2022-345, https://doi.org/10.5194/essd-15-1389-2023

Bjerge, K., Pinoy, N., Karstoft, H. & Høye, T. T. (2023). Field trials with automated moth monitoring in three different habitats of Denmark. Abstract fra 2023 Butterfly Conservation Symposium, Bedfordshire , Storbritannien.

Bjerge, K., Geissmann, Q., Alison, J., Mann, H. M. R., Høye, T. T., Dyrmann, M. & Karstoft, H. (2023). Hierarchical classification of insects with multitask learning and anomaly detection. Ecological Informatics, 77, Artikel 102278. https://doi.org/10.1016/j.ecoinf.2023.102278

Bjerge, K., Geissmann, Q., Alison, J., Mann, H. M. R., Høye, T. T., Dyrmann, M. & Karstoft, H. (2023). Hierarchical Classification of Insects with Multitask Learning and Anomaly Detection. bioRxiv. https://doi.org/10.1101/2023.06.29.546989

Gheisarnejad Chirani, M., Mosayebi, M., Rafiei Foroushani, M., Boudjadar, J. & Khooban, M. H. (2023). Hybrid Power Systems for Smart Marine Power Grids: Demonstration and Case Study. I Electric Transportation Systems in Smart Power Grids (s. 473-492). CRC Press. https://doi.org/10.1201/9781003293989

Cielecki, P. P., Hardenberg, M., Amariei, G., Henriksen, M. L., Hinge, M. & Klarskov, P. (2023). Identification of black plastics with terahertz time-domain spectroscopy and machine learning. Scientific Reports, 13(1), Artikel 22399. https://doi.org/10.1038/s41598-023-49765-z

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

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

Islam, M. T., Khan, H. A., Naveed, K., Nauman, A., Gulfam, S. M. & Kim, S. W. (2023). LUVS-Net: A Lightweight U-Net Vessel Segmentor for Retinal Vasculature Detection in Fundus Images. Electronics, 12(8), Artikel 1786. https://doi.org/10.3390/electronics12081786

Wang, Z., Chen, L., Chen, H. & Rehman, N. U. (2023). Monthly ship price forecasting based on multivariate variational mode decomposition. Engineering Applications of Artificial Intelligence, 125, Artikel 106698. https://doi.org/10.1016/j.engappai.2023.106698

Bjerge, K., Frigaard, C. E. & Karstoft, H. (2023). Object Detection of Small Insects in Time-Lapse Camera Recordings. Sensors, 23(16), Artikel 7242. https://doi.org/10.3390/s23167242

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Revideret 13.11.2025

AU Engineering