Institut for Elektro- og Computerteknologi

Aarhus Universitets segl

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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Rubak, J. A. B., Naveed, K., Jain, S., Esterle, L., Iosifidis, A. & Pauwels, R. (2025). Impact of Labeling Inaccuracy and Image Noise on Tooth Segmentation in Panoramic Radiographs using Federated, Centralized and Local Learning. ArXiv. https://doi.org/10.48550/arXiv.2509.06553
Jaume, G., Bozorgtabar, B., Ekenel, H. K., Thiran, J.-P. & Gabrani, M. (2018). Image-Level Attentional Context Modeling Using Nested-Graph Neural Networks.
Morales, T., Sarabakha, A. & Kayacan, E. (2020). Image Generation for Efficient Neural Network Training in Autonomous Drone Racing. I 2020 International Joint Conference on Neural Networks (IJCNN) Artikel 9206943 IEEE. https://doi.org/10.1109/IJCNN48605.2020.9206943
Rehman, N., Khan, M. M., Sohaib, M. I., Jehanzaib, M., Ehsan, S. & McDonald-Maier, K. (2014). Image fusion using multivariate and multidimensional EMD. I 2014 IEEE International Conference on Image Processing (ICIP) IEEE. https://doi.org/10.1109/icip.2014.7026035
Tu, G. J., Karstoft, H., Pedersen, L. J. & Jørgensen, E. (2015). Illumination and Reflectance Estimation with its Application in Foreground Detection. Sensors, 15(9), 21407-21426. https://doi.org/10.3390/s150921407
Asif, M. R., Kass, A., Larsen, J. J. & Christiansen, A. V. (2025). Identifying Induced Polarization Effects in TEM Data by Deep Learning. I 7th Asia Pacific Meeting on Near Surface Geoscience and Engineering, NSGE 2025 (s. 1-5). European Association of Geoscientists and Engineers, EAGE. https://doi.org/10.3997/2214-4609.202572056
Asif, M. R., Kass, A., Larsen, J. J. & Christiansen, A. V. (2024). Identification of Induced Polarization affected Transient Electromagnetic Data by Deep Learning. Poster-session præsenteret på AGU Fall meeting 2024, Washington DC, USA. https://ui.adsabs.harvard.edu/abs/2024AGUFMNS23B1231A/abstract
Jeppesen, J. H., Jacobsen, R. H., Nyholm Jørgensen, R., Halberg, A. & Toftegaard, T. S. (2017). Identification of High-Variation Fields based on Open Satellite Imagery. Advances in Animal Biosciences, 8(2), 388-393. https://doi.org/10.1017/S2040470017000693
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
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
Ali, M., Khan, A. & Rehman, N. U. (2017). Hybrid multiscale wind speed forecasting based on variational mode decomposition. International Transactions on Electrical Energy Systems, 28(1), e2466. https://doi.org/10.1002/etep.2466
Sridharan, K. S., Højlund, A., Sunde, N., Johnsen, E. L., Johansen, L. G., Beniczky, S. & Østergaard, K. (2016). How do treatments affect somatosensory processing in Parkinson's disease - A MEG study. Poster-session præsenteret på PhD Day 2016, Aarhus, Danmark.
Olesen, C. R., Nyholm Jørgensen, R., Laursen, M. S., Larsen, R. & Rosendahl Bjorholm, S. (2017). Høstdrab af rådyr: analyse af høstdrabsproblemets omfang i Danmark samt test af dronebåret losurin som afværgemetode. Danmarks Jægerforbund. http://udgivelser.jaegerforbundet.dk/2017/foldere-og-tryksager/hoestdrab-af-raadyr-analyse-af-hoestdrabsproblemets-omfang-i-danmark-samt-test-af-dronebaaret-losurin-som-afvaergemiddel/?page=2
Sørensen, C. A. G., Nørremark, M., Jørgensen, R., Jensen, K., Jensen, L. A. & Maagaard, J. (2007). Hortibot: Feasibility study of a plant nursing robot performing weeding operations - part IV: Paper No. 077019. I Ikke angivet ASABE - American Society of Agricultural and Biological Engineers. http://asae.frymulti.com/techpapers.asp?confid=min2007
Nørremark, M., Sørensen, C. A. G. & Jørgensen, R. N. (2006). HortiBot: Comparison of present and future phytotechnologies for weed control - part III: Paper No. 067023. I Proc. ASABE Annual Meeting http://asae.frymulti.com/request.asp?JID=5&AID=21017&CID=por2006&T=1
Jørgensen, R., Sørensen, C. A. G., Maagaard, J., Havn, I., Jensen, K., Søgaard, H. T. & Sørensen, L. B. (2007). HortiBot: A System Design of a Robotic Tool Carrier for High-tech PlantNursing. Agricultural Engineering International: CIGR Journal, IX. http://cigr-ejournal.tamu.edu/submissions/volume9/ATOE%2007%20006%20Jorgensen%2011July2007.pdf
Jørgensen, R., Sørensen, C. G., Pedersen, J. M., Havn, I., Jensen, K., Søgaard, H. T. & Sørensen, L. B. (2006). Hortibot: A system design of a robotic tool carrier for high-tech plant nursing. I Proc. Automation Technology for Off-Road Equipment (s. 13-22) https://cigrjournal.org/index.php/Ejounral/article/view/937/931
Sørensen, C. G., Jørgensen, R. N., Pedersen, J. M. & Nørremark, M. (2006). HortiBot: Application of Quality Function Deployment (QFD) Method for Horticultural Robotic Tool Carrier Design Planning - Part II: Paper No. 067021. I Proc. ASABE Annual Meeting http://asae.frymulti.com/request.asp?JID=5&AID=21015&CID=por2006&T=1
Jørgensen, R. N. & Vinstrup, A. B. (2005). Hortibot - A plant nursing robot. DaNet NewsLetter. https://drive.google.com/file/d/0B7n4HMXh8Cx3MXhxVWFyeTZYdjQ/view?resourcekey=0-qVqhxrsxiKtf5MQNz4aykQ
Jørgensen, R., Sørensen, C. G., Jensen, K., Søgaard, H. T., Pedersen, J. M., Sørensen, L. B., Havn, I., Sibbesen, S. & Nielsen, J. (2006). Hortibot: An Accessory Kit Transforming a Slope Mower into a Robotic Tool Carrier for High-Tech Plant Nursing - Part I: Paper No. 063082. I ASABE Annual Meeting ASABE - American Society of Agricultural and Biological Engineers. http://asae.frymulti.com/request.asp?JID=5&AID=20886&CID=por2006&T=1
Jørgensen, R. N. (2009). Horsens-robot sparer penge og hjælper miljøet: HORSENS - Forskere fra det tidligere Bygholm Forskningscenter repræsenterer i disse dage Danmark ved den store hollandske udstilling for mark-robotter, Field Robot Event. Horsens Folkeblad. http://www.horsens-folkeblad.dk/?artikel=2892
Green, O., Jørgensen, R. N., Sørensen, C. A. G., Kristensen, K., Bochtis, D. & Sørensen, C. A. G. (2010). Hjulbelastning og dæktryks påvirkning af græsudbyttet. I Indvielse af nye high-tech forskningsfaciliteter, Foulum, Danmark https://www.researchgate.net/publication/233725865_Hjulbelastning_og_daektryks_pavirkning_af_graesudbyttet
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. I NSG 2024 30th European Meeting of Environmental and Engineering Geophysics (s. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420111
Jørgensen, R., Nørremark, M., Sørensen, C. A. G. & Andersen, N. A. (2005). High-level control of robots for row crops. I Proc. XXXI CIOSTA-CIGR V cong. on Increasing Work Efficiency in Agriculture, Horticulture and Forestry, University of Hohenheim, Stuttgart, Germany. ISBN 3-00-016346-8 (s. 123-132) https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=a43aba0d78f0e4c0c89d8e4fd1df2dc2612e6985
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., 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
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
Malekian, R., Curran, K., Pedersen, C. F., Cao, B. & Qi, X. (2018). Guest Editorial Special Issue on Sensor Technologies for Connected Cars: Devices, Systems and Modeling. IEEE Sensors Journal, 18(12), 4775-4776. https://doi.org/10.1109/JSEN.2018.2830478
Skov, K., Mandrup, L., Johannsen, L. & Lysgaard, P. (2001). Grundlæggende EMC I: Fænomener og konstruktionsprincipper. I Grundlæggende EMC I: Fænomener og konstruktionsproncipper (1.3 udg., Bind T-306, s. 164).
Christiansen, M. P., Laursen, M. S., Nyholm Jørgensen, R., Skovsen, S. & Gislum, R. (2018). Ground Vehicle Mapping of Fields using LiDAR to Enable Prediction of Crop Biomass. I Proceedings of the 14th International Conference on Precision Agriculture Artikel 5145 International Society of Precision Agriculture. https://ispag.org/proceedings/?action=abstract&id=5145
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), Artikel e2024GL112094. https://doi.org/10.1029/2024GL112094
Griffiths, M. P., Grombacher, D., Mashhadi, S. R. & Larsen, J. J. (2024). Ground-truth Validation of T2 Estimates from Steady-state Surface NMR. Abstract fra AGU Fall meeting 2024, Washington DC, USA.
Wang, Z., Chen, L., Chen, H., Yang, J. & Rehman, N. U. (2025). Graph signal processing meets machine learning: Multi-scale spatial-temporal ensemble learning methodology for air quality forecasting. Expert Systems with Applications, 291, Artikel 128538. https://doi.org/10.1016/j.eswa.2025.128538
Nazari, M., Korshoej, A. R. & Rehman, N. U. (2024). Graph-Aided Multivariate Signal Decomposition. I International Conference on Frontiers of Signal Processing (ICFSP) (s. 169-173) https://doi.org/10.1109/ICFSP62546.2024.10785500
Madsen, S. L., Dyrmann, M., Nyholm Jørgensen, R. & Karstoft, H. (2019). Generating artificial images of plant seedlings using generative adversarial networks. Biosystems Engineering, 187, 147-159. https://doi.org/10.1016/j.biosystemseng.2019.09.005
Mahapatra, D., Bozorgtabar, B., Ge, Z. & Reyes, M. (2024). GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification. Medical Image Analysis, 93, Artikel 103075. https://doi.org/10.1016/j.media.2023.103075
Nielsen, M. R., Laursen, M. S., Jonassen, M. S., Nielsen, K. & Nyholm Jørgensen, R. (2013). Gall mite inspection on dormant black currant buds using machine vision. I Precision Agriculture 2013 - Papers Presented at the 9th European Conference on Precision Agriculture, ECPA 2013 (s. 517-524) http://www.scopus.com/inward/record.url?scp=84893421680&partnerID=8YFLogxK
Nyholm Jørgensen, R., Sørensen, R. A., Laursen, M. S., Rasmussen, J. & Nielsen, J. (2017). FutureCropping Generering af tidselkort med Pix4D, DeepLearning og QGIS 18AUG2017. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=3X8h4U4o2-o
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), Artikel 116142. https://doi.org/10.1016/j.measurement.2024.116142
Bertelsen, K. K., Duzel, J., Nielsen, S. H. & Jørgensen, R. N. (2011). FruitGrowth - Gasburning in Orchards - Environment friendly weed control. http://www.horteam-expo.dk/
Wu, S., Deng, S., Wei, X., Asif, M. R., Vignoli, G. & Farquharson, C. G. (2025). Frontiers in electromagnetic geophysics - Introduction. Geophysics, 90(3), WAi-WAii. https://doi.org/10.1190/geo2025-0312-spseintro.1
Jensen, K., Bøgild, A., Nielsen, S. H., Christiansen, M. P. & Jørgensen, R. N. (2011). FroboMind, proposing a conceptual architecture for agricultural field robot navigation. http://www.njf.nu/site/seminarRedirect.asp?intSeminarID=441&p=1004
Grombacher, D., Griffiths, M. P., Liu, L., Vang, M. & Larsen, J. J. (2022). Frequency Shifting Steady-State Surface NMR Signals to Avoid Problematic Narrowband-Noise Sources. Geophysical Research Letters, 49(7), Artikel e2021GL097402. https://doi.org/10.1029/2021GL097402
Sveistrup, D., Jørgensen, R. N., Green, O., Nørremark, M. & Sørensen, C. A. G. (2011). Fremtidens markforsøg. http://pure.agrsci.dk:8080/research/fremtidens_markforsoeg(4162764)/
Bach, P. D., Jørgensen, R. N. & Jensen, K. (2012). Fremtidens landbrugsmaskiner kører selv. Dagbladet Holstebro-Struer, 14-15. https://docs.google.com/open?id=0B7n4HMXh8Cx3Qk1DTHRfMHo2ZEU
Jørgensen, R. (2007). Fremtiden for Forskningscenter Bygholm. Horsens Folkeblad, 2.
Gul, S., Siddiqui, M. F. & Rehman, N. U. (2019). FPGA Based Real-Time Implementation of Online EMD With Fixed Point Architecture. IEEE Access, 7, 176565-176577. https://doi.org/10.1109/access.2019.2957819
Malik, Q. W., Rehman, N. U., Gull, S., Ehsan, S. & McDonald-Maier, K. D. (2019). FPGA-Based Real-Time Implementation of Bivariate Empirical Mode Decomposition. Circuits, Systems, and Signal Processing, 38(1), 118-137. https://doi.org/10.1007/s00034-018-0844-2
Gul, S., Siddiqui, M. F. & Rehman, N. U. (2020). FPGA-Based Design for Online Computation of Multivariate Empirical Mode Decomposition. IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 67(12), 5040-5050. Artikel 9159690. https://doi.org/10.1109/TCSI.2020.3012351
Jensen, T., Green, O., Munkholm, L. J. & Karstoft, H. (2016). Fourier and granulometry methods on 3D images of soil surfaces for evaluating soil aggregate size distribution. American Society of Agricultural and Biological Engineers. Transactions, 32(5), 609-615. https://doi.org/10.13031/aea.32.10938

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AU Engineering