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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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

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

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

Jensen, M. H., Rasmussen, M., Mohamad, N., Dyrskog, S. E., Thorup, L., Mikic, N., Wismann, J., Grønhøj, M. H., Rom Poulsen, F., Nazari, M., Rehman, N. U., Simonsen, C. Z. & Korshoej, A. R. (2023). Safety, harm, and efficacy of IRRAflow® versus external ventricular drainage for intraventricular hemorrhage: A randomized clinical trial. medRxiv. https://doi.org/10.1101/2023.07.08.23292286

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), Article 22399. https://doi.org/10.1038/s41598-023-49765-z

Nawoya, S., Ssemakula, F., Akol, R., Geissmann, Q., Karstoft, H., Bjerge, K., Mwikirize, C., Katumba, A. & Gebreyesus, G. (2024). Computer vision and deep learning in insects for food and feed production: A review. Computers and Electronics in Agriculture, 216, Article 108503. https://doi.org/10.1016/j.compag.2023.108503

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

Rafiei Foroushani, M., Tran, D. T. & Iosifidis, A. (2023). Recognition of Defective Mineral Wool Using Pruned ResNet Models. In H. Dorksen, S. Scanzio, J. Jasperneite, L. Wisniewski, K. F. Man, T. Sauter, L. Seno, H. Trsek & V. Vyatkin (Eds.), 2023 IEEE 21st International Conference on Industrial Informatics (INDIN) IEEE. https://doi.org/10.1109/INDIN51400.2023.10217993

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

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

Skovsen, S. K., Kutugata, M., Jennewein, J., Reberg-Horton, C. S. & Mirsky, S. B. (2023). Detailed Species Competition Mapping of Mixed Cover Crop Species Using Tractor Mounted Color Camera and Computer Vision. Abstract from 2023 ASA/CSSA/SSSA International Annual Meeting, St. Louis, Missouri, United States.

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. (pp. 1-22). Geoscientific Instrumentation, Methods and Data Systems https://doi.org/10.5194/gi-2023-5

Vang, M., Grombacher, D., Griffiths, M. P., Liu, L. & Larsen, J. J. (2023). Technical note: High-density mapping of regional groundwater tables with steady-state surface nuclear magnetic resonance - three Danish case studies. Hydrology and Earth System Sciences, 27(16), 3115-3124. https://doi.org/10.5194/hess-27-3115-2023

Lillelund, C. M., Magris, M. & Pedersen, C. F. (2023). Uncertainty Estimation in Deep Bayesian Survival Models. In IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI’23) IEEE. https://doi.org/10.1109/BHI58575.2023.10313466

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. Article e2335247. https://doi.org/10.1001/jamanetworkopen.2023.35247

Dobbs, A. M., Ginn, D., Skovsen, S. K., Yadav, R., Jha, P., Bagavathiannan, M. V., Mirsky, S. B., Reberg-Horton, C. S. & Leon, R. G. (2023). Using structure-from-motion to estimate cover crop biomass and characterize canopy structure. Field Crops Research, 302, Article 109099. https://doi.org/10.1016/j.fcr.2023.109099

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. In APPLICATION OF GEOPHYSICS TO ENGINEERING AND ENVIRONMENTAL PROBLEMS: SYMPOSIUM. 35TH 2023. (SAGEEP 2023) (pp. 82-82). Curran Associates.

Lillelund, C. M., Pannullo, F., Jakobsen, M. O. & Pedersen, C. F. (2023). Predicting Survival Time of Ball Bearings in the Presence of Censoring. In AAAI Symposium on Survival Prediction: Algorithms, Challenges, and Applications (SPACA) AAAI Press.

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), Article 711. https://doi.org/10.1007/s42979-023-02244-8

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, Article 102278. https://doi.org/10.1016/j.ecoinf.2023.102278

Jensen, M. H., Nazari, M., Gu, C., Rasmussen, M., Dyrskog, S. E., Simonsen, C. Z., Grønhøj, M. H., Rom Poulsen, F., Rehman, N. U. & Korshoej, A. R. (2023). Reliability and Performance of the IRRAflow® System for Intracranial Lavage and Evacuation of Hematomas - A Technical Note. https://doi.org/10.1101/2023.07.07.23292372

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, No. 2023-0543874, 8 p., Aug 23, 2023. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

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

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). https://doi.org/10.1371/journal.pstr.0000051

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

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

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, Article 110553. https://doi.org/10.1016/j.ymssp.2023.110553

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, Article 106698. https://doi.org/10.1016/j.engappai.2023.106698

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

Iqbal, S., Naveed, K., Naqvi, S. S., Naveed, A. & Khan, T. M. (2023). Robust retinal blood vessel segmentation using a patch-based statistical adaptive multi-scale line detector. Digital Signal Processing: A Review Journal, 139, Article 104075. https://doi.org/10.1016/j.dsp.2023.104075

Liu, L., Grombacher, D., Griffiths, M., Vang, M. & Larsen, J. J. (2023). Signal Processing Steady-State Surface NMR Data. IEEE Transactions on Instrumentation and Measurement, 72, Article 6502313. https://doi.org/10.1109/TIM.2023.3264033

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), Article 1786. https://doi.org/10.3390/electronics12081786

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