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Department of Electrical and Computer Engineering

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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Nazari, M. (2025). Modeling Temporal Characteristics and Topological Structures in Data-driven Signal. [PhD dissertation, Aarhus University].

Amer, A., Felsager, D., Brodskiy, Y. & Sarabakha, A. (2025). Modelling of Underwater Vehicles using Physics-Informed Neural Networks with Control. In International Joint Conference on Neural Networks, IJCNN 2025 - Proceedings IEEE. https://doi.org/10.1109/IJCNN64981.2025.11228873

Deria, A., Mahapatra, D., Bozorgtabar, B., Chakraborty, M., Chakraborty, S. & Roy, S. (2025). MuGa-VTON: Multi-Garment Virtual Try-On via Diffusion Transformers with Prompt Customization.

Sejersen, J. L. F., Sarabakha, A., Plagborg Bak Sørensen, K. & Høigaard Jensen, J. (2025). Multi-Agent Path Planning in Complex Environments using Gaussian Belief Propagation with Global Path Finding. 4359-4365. Paper presented at 2025 IEEE International Conference on Robotics and Automation (ICRA) , Atlanta, Georgia, United States. https://doi.org/10.1109/ICRA55743.2025.11128006

Mahapatra, D., Jimeno Yepes, A., Bozorgtabar, B., Roy, S., Ge, Z. & Reyes, M. (2025). Multi-Label Generalized Zero Shot Chest X-Ray Classification by Combining Image-Text Information With Feature Disentanglement. IEEE Transactions on Medical Imaging, 44(1), 31-43. https://doi.org/10.1109/TMI.2024.3429471

Naveed, K., de Freitas, B. N. & Pauwels, R. (2025). Naada: A Noise-Aware Attention Denoising Autoencoder for Dental Panoramic Radiographs.

Böttner, C., Jakobsen, F. W., Nielsen, T., Winsborrow, M., Polteau, S., Mazzini, A., Planke, S., Andresen, K. J., Millinge, O. J. S., Asif, M. R., Laberg, J. S., Hopper, J., Myklebust, R. & Seidenkrantz, M. S. (2025). Natural hydrocarbon seepage at the Northeast Greenland continental shelf. Communications Earth and Environment, 6(1), Article 879. https://doi.org/10.1038/s43247-025-02932-8

Li, C., Bozorgtabar, B., Ping, Y., Huang, P. & Qin, J. (2025). Positive Semi-definite Latent Factor Grouping-Boosted Cluster-reasoning Instance Disentangled Learning for WSI Representation.

Nawoya, S., Geissmann, Q., Karstoft, H., Bjerge, K., Akol, R., Katumba, A., Mwikirize, C. & Gebreyesus, G. (2025). Prediction of black soldier fly larval sex and morphological traits using computer vision and deep learning. Smart Agricultural Technology, 11, Article 100953. https://doi.org/10.1016/j.atech.2025.100953

Vray, G., Tomar, D., Gao, X., Thiran, J.-P., Shelhamer, E. & Bozorgtabar, B. (2025). ReservoirTTA: Prolonged Test-time Adaptation for Evolving and Recurring Domains. Curran Associates, Inc. Advances in Neural Information Processing Systems Vol. 38

Chakraborty, S., Kumar, K., Deria, A., Mahapatra, D., Bozorgtabar, B. & Roy, S. (2025). Robust semantic learning for precise medical image segmentation. Biomedical Signal Processing and Control, 110, Article 108251. https://doi.org/10.1016/j.bspc.2025.108251

Ong, S.-Q., Pinoy, N., Hui Lin, M., Bjerge, K., Peris-Felipo, F. J., Lind, R., P. Cuff, J., M. Cook, S. & Høye, T. T. (2025). ScannerVision: Scanner-based image acquisition of medically important arthropods for the development of computer vision and deep learning models. Current Research in Parasitology & Vector-Borne Diseases, 7, Article 100268. https://doi.org/10.1016/j.crpvbd.2025.100268

Liu, S., Lang, X., Wu, J. & Rehman, N. U. (2025). Selective Noise Empirical Mode Decomposition. IEEE Signal Processing Letters, 32, 2823-2827. https://doi.org/10.1109/LSP.2025.3588082

Kumar, K., Chakraborty, S., Mahapatra, D., Bozorgtabar, B. & Roy, S. (2025). Self-Supervised Anomaly Segmentation via Diffusion Models with Dynamic Transformer UNet. In Proceedings - 2025 IEEE Winter Conference on Applications of Computer Vision, WACV 2025 (pp. 7928-7938). IEEE. https://doi.org/10.1109/WACV61041.2025.00770

Vahedifar, M. A., Akhtarshenas, A., Rafatpanah, M. M. & Sabbaghian, M. (2025). Shapley-Based Data Valuation with Mutual Information: A Key to Modified K-Nearest Neighbors. In 2025 IEEE 35th International Workshop on Machine Learning for Signal Processing (MLSP) https://doi.org/10.1109/MLSP62443.2025.11204262

Vahedifar, M. A. & Zhang, Q. (2025). Signal Prediction for Loss Mitigation in Tactile Internet: A Leader-Follower Game-Theoretic Approach. In 35th IEEE International Workshop on Machine Learning for Signal Processing: Signal Processing in the Age of Lorge Language Models, MLSP 2025 IEEE Computer Society Press. https://doi.org/10.1109/MLSP62443.2025.11204284

Tomar, D., Vray, G., Mahapatra, D., Roy, S., Thiran, J. P. & Bozorgtabar, B. (2025). Slide-Level Prompt Learning with Vision Language Models for Few-Shot Multiple Instance Learning in Histopathology. In ISBI 2025 - 2025 IEEE 22nd International Symposium on Biomedical Imaging, Proceedings IEEE Computer Society Press. https://doi.org/10.1109/ISBI60581.2025.10980748

Nazari, M., Korshoej, A. R. & Rehman, N. U. (2025). Successive Jump and Mode Decomposition. (pp. 2622-2626). https://doi.org/10.23919/EUSIPCO63237.2025.11226714

Rafiei Foroushani, M., Asif, M. R., Nørremark, M. & Grøn Sørensen, C. (2025). Temporal and Spatial Analysis of Critical Field Points Using High-Resolution Soil Water Content Estimation Employing Remote Sensing and Deep-Learning. Abstract from EGU General Assembly 2025, Vienna, Austria. https://doi.org/10.5194/egusphere-egu25-18129

Bjerge, K., Karstoft, H. & Høye, T. T. (2025). Towards edge processing of images from insect camera traps. Remote Sensing in Ecology and Conservation, 11(5), 573-589. https://doi.org/10.1002/rse2.70007

Mikutavicius, R., Álvarez-Tuñón, O., Brodskiy, Y. & Sarabakha, A. (2025). Towards End-to-End Underwater vSLAM Using Neural Radiance Fields. In OCEANS 2025 Brest, OCEANS 2025 IEEE. https://doi.org/10.1109/OCEANS58557.2025.11104336

Kass, M. A., Ruganiza, A. K., Grombacher, D., Vela, I., Elias, R., Ondicho, A., Griffiths, M. P. & Pedersen, J. B. (2025). Transient Electromagnetic Surveys for Groundwater Investigations Near the Kakuma Refugee Camp, Kenya. https://doi.org/10.3997/2214-4609.202520072

Tang, F., An, X., Yang, H., Xie, Y., Yang, K., Hu, M., Cheng, Z., Zhou, X., Ran, Z., Razzak, I., Feng, Z., Bozorgtabar, B., Deng, J. & Ge, Z. (2025). Unifying Image and Video Understanding in One Vision Encoder. Paper presented at The Thirty-ninth Annual Conference on Neural Information Processing Systems, San Diego, California, United States. https://openreview.net/pdf/46f20263cc2abbd139b0f9be3ada52e0fd7427d5.pdf

Dang, V. H., Redder, A., Pham, H. X., Sarabakha, A. & Kayacan, E. (2025). VDS-Nav: Volumetric Depth-Based Safe Navigation for Aerial Robots–Bridging the Sim-to-Real Gap. IEEE Robotics and Automation Letters, 10(10), 11038-11045. https://doi.org/10.1109/LRA.2025.3606806

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., 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

Rafiei Foroushani, M. (2024). Advancing Computer Vision in Irregular Texture Product Analysis. [PhD dissertation, Aarhus University]. Aarhus Universitet.

Mahapatra, D., Tennakoon, R., George, Y., Roy, S., Bozorgtabar, B., Ge, Z. & Reyes, M. (2024). ALFREDO: Active Learning with FeatuRe disEntangelement and DOmain adaptation for medical image classification. Medical Image Analysis, 97, Article 103261. https://doi.org/10.1016/j.media.2024.103261

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#

Todnem Bach Christensen, L., 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. In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando, FL, USA (pp. 1-4). IEEE. https://doi.org/10.1109/EMBC53108.2024.10781771

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

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

Asif, MR., Larsen, JJ. & Christiansen, AV. (2024). Automated Processing of Time-Domain Electromagnetic Data Influenced by Induced Polarization Effects. In NSG 2024 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420140

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Christiansen, A. V. (2024). Clustering on SNMR and TEM parameters over a saline-freshwater interface to resolve hydrogeological layers. In NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420102

Mahapatra, D., Bozorgtabar, B., Ge, Z., Reyes, M. & Thiran, J. P. (2024). Combining Graph Transformers Based Multi-Label Active Learning and Informative Data Augmentation for Chest Xray Classification. Proceedings of the AAAI Conference on Artificial Intelligence, 38(19), 21378-21386. https://doi.org/10.1609/aaai.v38i19.30133

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

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

Qiao, Z., Pham, X. H., Ramasamy, S., Jiang, X., Kayacan, E. & Sarabakha, A. (2024). Continual Learning for Robust Gate Detection under Dynamic Lighting in Autonomous Drone Racing. In 2024 International Joint Conference on Neural Networks, IJCNN 2024 - Proceedings IEEE. https://doi.org/10.1109/ijcnn60899.2024.10649903

Carreto Picón, G., Oleksiienko, I., Morsing, L. H., Bakhtiarnia, A. & Iosifidis, A. (2024). Continual Low-Rank Scaled Dot-product Attention. https://doi.org/10.48550/arXiv.2412.03214

Lebailly, T., Stegmüller, T., Bozorgtabar, B., Thiran, J. P. & Tuytelaars, T. (2024). CRIBO: SELF-SUPERVISED LEARNING VIA CROSS-IMAGE OBJECT-LEVEL BOOTSTRAPPING. Paper presented at 12th International Conference on Learning Representations, ICLR 2024, Hybrid, Vienna, Austria.

Millinge, O., Böttner, C. & Asif, MR. (2024). Deep Learning based Identification of Oil-Slick Emissions in the Arctic Using Satellite SAR Data. In NSG 2024 4th Conference on Airborne, Drone and Robotic Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420159

So, P., Sarabakha, A., Wu, F., Culha, U., Abu-Dakka, F. & Haddadin, S. (2024). Digital Robot Judge: Building a Task-centric Performance Database of Real-World Manipulation With Electronic Task Boards. IEEE Robotics and Automation Magazine, 31(4), 32-44. https://doi.org/10.1109/MRA.2023.3336473

Vray, G., Tomar, D., Bozorgtabar, B. & Thiran, J. P. (2024). Distill-SODA: Distilling Self-Supervised Vision Transformer for Source-Free Open-Set Domain Adaptation in Computational Pathology. IEEE Transactions on Medical Imaging, 43(5), 2021-2032. https://doi.org/10.1109/TMI.2024.3355645

Lakshminarayanan, S., Duecker, D., Sarabakha, A., Ganguly, A., Takayama, L. & Haddadin, S. (2024). Estimation of External Force acting on Underwater Robots. In 2024 IEEE 20th International Conference on Automation Science and Engineering, CASE 2024 (pp. 3125-3131). IEEE. https://doi.org/10.1109/CASE59546.2024.10711608

Mashhadi, S. R., Grombacher, D., Pedersen, J. B., Jørgensen, F., Andersen, T. R. & Griffiths, M. P. (2024). Estimation of hydraulic conductivity variations within glacial sediments at Endelave island by borehole NMR data. In 30th European Meeting of Environmental and Engineering Geophysics, Held at the Near Surface Geoscience Conference and Exhibition 2024, NSG 2024 European Association of Geoscientists and Engineers, EAGE. https://doi.org/10.3997/2214-4609.202420047

Grombacher, D., Griffiths, M. P. & Maurya, P. K. (2024). Estimation of transmitter-receiver separation for mobile ground-based transient electromagnetic systems using on-time gates. Abstract from AGU Fall meeting 2024, Washington DC, United States.

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Christiansen, A. V. (2024). Extrapolating sparse SNMR data sets onto dense TEM coverage using spatially variable correlations. Abstract from AGU Fall meeting 2024, Washington DC, United States.

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

Griffiths, M. P. & Hardenberg, M. (2024). Feasibility study of steady-state surface NMR with adiabatic pulses. Paper presented at EAGE Near Surface Geoscience, Helsinki, Finland.

Hardenberg, M., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2024). Feasibility study of steady-state surface NMR with adiabatic pulses. In NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (pp. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420051

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