Institut for Elektro- og Computerteknologi

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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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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. 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
Oleksiienko, I., Nousi, P., Passalis, N., Tefas, A. & Iosifidis, A. (2023). Variational Voxel Pseudo Image Tracking. I 2023 IEEE Symposium Series on Computational Intelligence (SSCI) (s. 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. Artikel 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. I 2023 21st International Conference on Advanced Robotics (ICAR) (s. 431-438). IEEE. https://doi.org/10.1109/ICAR58858.2023.10406329
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
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
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
Naveed, K., Meldgaard Madsen, L., Grombacher, D. & Larsen, J. J. (2023). Variational Mode Decomposition-Based Processing of Time-Domain Induced Polarization Data. Abstract fra NSG2023 29th European Meeting of Environmental and Engineering Geophysics, Edinburgh , Storbritannien. 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), Artikel 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, Artikel 108503. https://doi.org/10.1016/j.compag.2023.108503
Rafiei Foroushani, M., Tran, D. T. & Iosifidis, A. (2023). Recognition of Defective Mineral Wool Using Pruned ResNet Models. I H. Dorksen, S. Scanzio, J. Jasperneite, L. Wisniewski, K. F. Man, T. Sauter, L. Seno, H. Trsek & V. Vyatkin (red.), 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. I 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
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
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. I 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. Artikel e2335247. https://doi.org/10.1001/jamanetworkopen.2023.35247
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.
Lillelund, C. M., Pannullo, F., Jakobsen, M. O. & Pedersen, C. F. (2023). Predicting Survival Time of Ball Bearings in the Presence of Censoring. I 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), Artikel 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, Artikel 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, Nr. 2023-0543874, 8 s., 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 fra 2023 Butterfly Conservation Symposium, Bedfordshire , Storbritannien.
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
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), Artikel 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, Artikel 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, Artikel 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, Artikel 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, Artikel 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), Artikel 1786. https://doi.org/10.3390/electronics12081786
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
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
Oleksiienko, I. & Iosifidis, A. (2022). 3D object detection and tracking. I A. Iosifidis & A. Tefa (red.), Deep Learning for Robot Perception and Cognition (s. 313-340). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00018-X
McLachlan, P. J., Khare, S. K., Grombacher, D., Larsen, J. J., Christensen, A. & Zamora Luria, J. C. (2022). On The Presence of Correlated Noise in Transient Electromagnetic (Tem) Monitoring Data. I NSG2022 28th European Meeting of Environmental and Engineering Geophysics (s. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202220119
McLachlan, P. J., Khare, S. K., Grombacher, D., Larsen, J. J., A. Christiensen, A. & Luria, J. C. Z. (2022). On The Presence of Correlated Noise in Transient Electromagnetic (Tem) Monitoring Data. 1-5. Abstract fra NSG2022 28th European Meeting of Environmental and Engineering Geophysics, Belgrade , Serbien. https://doi.org/10.3997/2214-4609.202220119
Asif, M. R., Larsen, J. J., Auken, E. & Christiansen, A. V. (2022). Deep Convolutional Auto-Encoder for Automated Processing of Airborne Time-Domain Electromagnetic Data. 1-5. Afhandling præsenteret på NSG2022 3rd Conference on Airborne, Drone and Robotic Geophysics, Beograd, Serbien. https://doi.org/10.3997/2214-4609.202220038
Asif, M. R., Bording, T. S., Barfod, A. S., Auken, E. & Larsen, J. J. (2020). Effect of data normalization on neural networks for the forward modelling of transient electromagnetic data. I 26th European Meeting of Environmental and Engineering Geophysics, Held at Near Surface Geoscience 2020 Artikel 061 European Association of Geoscientists and Engineers, EAGE. https://doi.org/10.3997/2214-4609.202020061
Asif, M. R., Maurya, P. K., Larsen, J. J. & Christiansen, A. V. (2022). Investigating the Integration of Neural Networks in Least-Squares Method for Airborne Electromagnetic Data Inversion. 1-5. Afhandling præsenteret på NSG2022 3rd Conference on Airborne, Drone and Robotic Geophysics, Beograd, Serbien. https://doi.org/10.3997/2214-4609.202220034
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
Larsen, J. J., Lévy, L. & Asif, M. R. (2022). Removal of powerline noise in geophysical data sets with a scientific machine-learning based approach. IEEE Transactions on Geoscience and Remote Sensing, 60, Artikel 5923410. https://doi.org/10.1109/TGRS.2022.3223737
Liu, L., Griffiths, M. P., Vang, M., Grombacher, D. J. & Larsen, J. J. (2021). Is it redundant to use model-based subtraction together with the reference noise cancellation? I 27th European Meeting of Environmental and Engineering Geophysics, Held at Near Surface Geoscience Conference and Exhibition 2021, NSG 2021 EAGE Publishing BV. https://doi.org/10.3997/2214-4609.202120108
Kass, M. A., Grombacher, D., Griffiths, M., Vang, M. Ø., Liu, L. & Larsen, J. J. (2022). A steady-state approach to surface nuclear magnetic resonance. I Proceedings of the Symposium on the Application of Geophyics to Engineering and Environmental Problems, SAGEEP (s. 54). J and N Group, Ltd.. https://www.eegs.org/assets/docs/Symposium/2022SAGEEP/AbstractsbyAuthor/Kass%2C%20A%20STEADY-STATE%20APPROACH%20TO%20SURFACE%20NUCLEAR%20MAGNETIC%20RESONANCE%20-%20SAGEEP%202022%20-%20205367449.pdf
Laursen, S. R. L., Holm, H. A. & Nielsen, S. H. (2022). Heart rate-based dynamic sound intervention - a pilot study. I Proceedings of the EUROREGIO/BNAM2022 Conference: Joimt Acoustics Conference (s. 473-481). https://www.conforg.fr/erbnam2022/output_directory/data/articles/000032.pdf
Bjerge, K., Frigaard, C. E. & Karstoft, H. (2022). Motion Informed Object Detection of Small Insects in Time-lapse Camera Recordings. arxiv.org. https://arxiv.org/abs/2212.00423

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AU Engineering