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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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Gislum, R., Thomsen, I. K., Hansen, E. M., Mortensen, A. K., Larsen, R. & Olesen, J. E. (2022). Endelig rapport i pilotprojekt om biomasse. Aarhus Universitet - DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug

Andersen, K. F., Pham, H. X., Ugurlu, H. I. & Kayacan, E. (2022). Event-based Navigation for Autonomous Drone Racing with Sparse Gated Recurrent Network. In 2022 European Control Conference (ECC) (pp. 1342-1348). IEEE. https://doi.org/10.23919/ECC55457.2022.9838538

Kjaer-Rasmussen, A., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2022). Fast removal of powerline harmonic noise from surface NMR datasets using a projection-based approach on graphical processing units. IEEE Geoscience and Remote Sensing Letters, 19, Article 8024005. https://doi.org/10.1109/LGRS.2021.3118064

Chumachenko, K., Iosifidis, A. & Gabbouj, M. (2022). Feedforward Neural Networks Initialization based on Discriminant Learning. Neural Networks, 146, 220-229. https://doi.org/10.1016/j.neunet.2021.11.020

Nielsen, A. H., Iosifidis, A. & Karstoft, H. (2022). Forecasting large-scale circulation regimes using deformable convolutional neural networks and global spatiotemporal climate data. Scientific Reports, 12(1), Article 8395. https://doi.org/10.1038/s41598-022-12167-8

Griffiths, M. P., Grombacher, D., Liu, L., Vang, M. Ø. & Larsen, J. J. (2022). Forward Modeling Steady-State Free Precession in Surface NMR. IEEE Geoscience and Remote Sensing Letters, 60, Article 4513510. https://doi.org/10.1109/TGRS.2022.3221624

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), Article e2021GL097402. https://doi.org/10.1029/2021GL097402

Heidari, N., Hedegaard Morsing, L. & Iosifidis, A. (2022). Graph convolutional networks. In A. Iosifidis & A. Tefas (Eds.), Deep Learning for Robot Perception and Cognition (pp. 71-99). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00009-9

Laakom, F., Raitoharju, J., Passalis, N., Iosifidis, A. & Gabbouj, M. (2022). Graph Embedding with Data Uncertainty. IEEE Access, 10, 24232-24239. https://doi.org/10.1109/ACCESS.2022.3155233

Li, N., Iosifidis, A. & Zhang, Q. (2022). Graph Reinforcement Learning-based CNN Inference Offloading in Dynamic Edge Computing. In 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings (pp. 982-987). IEEE. https://doi.org/10.1109/GLOBECOM48099.2022.10001067

Gaikwad, N. B., Khare, S. K., Satpute, N. & Keskar, A. G. (2022). Hardware Implementation of High-performance Classifiers for Edge Gateway of Smart Automobile. In Proceedings of PCEMS 2022 - 1st International Conference on the Paradigm Shifts in Communication, Embedded Systems, Machine Learning and Signal Processing (pp. 74-77). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PCEMS55161.2022.9808049

Laursen, S. R. L., Holm, H. A. & Nielsen, S. H. (2022). Heart rate-based dynamic sound intervention - a pilot study. In Proceedings of the EUROREGIO/BNAM2022 Conference: Joimt Acoustics Conference (pp. 473-481). https://www.conforg.fr/erbnam2022/output_directory/data/articles/000032.pdf

Morsing, L. H., Heidari, N. & Iosifidis, A. (2022). Human Activity Recognition. In A. Iosifidis & A. Tefas (Eds.), Deep Learning for Robot Perception and Cognition (pp. 341-370). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00019-1

Pimentel de Figueiredo, R., Le Fevre Sejersen, J., Grimm Hansen, J. & Brandão, M. (2022). Integrated design-sense-plan architecture for autonomous geometric-semantic mapping with UAVs. Frontiers in Robotics and AI, 9, Article 911974. https://doi.org/10.3389/frobt.2022.911974

Asif, M. R., Foged, N., Maurya, P. K., Grombacher, D. J., Christiansen, A. V., Auken, E. & Larsen, J. J. (2022). Integrating neural networks in least-squares inversion of airborne time-domain electromagnetic data. Geophysics, 87(4), E177-E187. https://doi.org/10.1190/geo2021-0335.1

Iosifidis, A. & Tefas, A. (2022). Introduction. In A. Iosifidis & A. Tefas (Eds.), Deep Learning for Robot Perception and Cognition Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00006-3

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. Paper presented at NSG2022 3rd Conference on Airborne, Drone and Robotic Geophysics, Beograd, Serbia. https://doi.org/10.3997/2214-4609.202220034

Sadiq, M. T., Yu, X., Yuan, Z., Aziz, M. Z., Rehman, N. U., Ding, W. & Xiao, G. (2022). Motor Imagery BCI Classification Based on Multivariate Variational Mode Decomposition. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(5), 1177-1189. Advance online publication. https://doi.org/10.1109/tetci.2022.3147030

Shabani, M., Tran, D. T., Magris, M., Kanniainen, J. & Iosifidis, A. (2022). Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction. In 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings (pp. 1487-1491). IEEE. https://doi.org/10.23919/EUSIPCO55093.2022.9909957

Dobbs, A. M., Ginn, D., Skovsen, S. K., Bagavathiannan, M. V., Mirsky, S. B., Reberg-Horton, C. S. & Leon, R. G. (2022). New directions in weed management and research using 3D imaging. Weed Science, 70(6), 641-647. https://doi.org/10.1017/wsc.2022.56

Chumachenko, K., Gabbouj, M. & Iosifidis, A. (2022). Object detection and tracking. In A. Iosifidis & A. Tefas (Eds.), Deep Learning for Robot Perception and Cognition (pp. 243-278). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00016-6

Gislum, R., Holst, N., Mortensen, A. K., Larsen, R., Andersen, M. N., Thomsen, I. K. & Hansen, E. M., (2022). Omregningsfaktor fra NDVI og NDRE til kg N optag/ha, No. 2022-0389751, 9 p., Sept 19, 2022. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Pham, X. H., Sarabakha, A., Odnoshyvkin, M. & Kayacan, E. (2022). PencilNet: Zero-Shot Sim-to-Real Transfer Learning for Robust Gate Perception in Autonomous Drone Racing. IEEE Robotics and Automation Letters, 7(4), 11847 - 11854. https://doi.org/10.1109/LRA.2022.3207545

Kragh, M. F., Rimestad, J., Lassen, J. T., Berntsen, J. & Karstoft, H. (2022). Predicting embryo viability based on self-supervised alignment of time-lapse videos. IEEE Transactions on Medical Imaging, 41(2), 465-475. Advance online publication. https://doi.org/10.1109/TMI.2021.3116986

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2022). Progressive and compressive learning. In A. Iosifidis & A. Tefas (Eds.), Deep Learning for Robot Perception and Cognition (pp. 187-220). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00014-2

Bjerge, K., Mann, H. M. R. & Høye, T. T. (2022). Real-time insect tracking and monitoring with computer vision and deep learning. Remote Sensing in Ecology and Conservation, 8(3), 315-327. Advance online publication. https://doi.org/10.1002/rse2.245

Iqbal, S., Khan, T. M., Naveed, K., Naqvi, S. S. & Nawaz, S. J. (2022). Recent trends and advances in fundus image analysis: A review. Computers in Biology and Medicine, 151, Article 106277. https://doi.org/10.1016/j.compbiomed.2022.106277

Li, N., Iosifidis, A. & Zhang, Q. (2022). Receptive Field-based Segmentation for Distributed CNN Inference Acceleration in Collaborative Edge Computing. In ICC 2022 - IEEE International Conference on Communications (pp. 4281-4286). IEEE. https://doi.org/10.1109/ICC45855.2022.9838547

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2022). Remote Multilinear Compressive Learning with Adaptive Compression. IEEE Internet of Things Journal, 9(9), 6905-6913. Advance online publication. https://doi.org/10.1109/jiot.2021.3114743

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, Article 5923410. https://doi.org/10.1109/TGRS.2022.3223737

Heidari, N. (2022). Representation Learning for Graph-Structured Data Analysis. Aarhus Universitet.

Kremer, T., Irons, T., Müller-Petke, M. & Juul Larsen, J. (2022). Review of Acquisition and Signal Processing Methods for Electromagnetic Noise Reduction and Retrieval of Surface Nuclear Magnetic Resonance Parameters. Surveys in Geophysics, 43(4), 999-1053. https://doi.org/10.1007/s10712-022-09695-3

Gislum, R., Jørgensen, R., Mortensen, A. K. & Mikkelsen, B. (2022). Roboter im Ackerbau - Entwicklung aus der Nische. 39. Abstract from DLG-Technikertagung 2022.

Xu, L., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2022). Saliency-based Weighted Multilabel Linear Discriminant Analysis. IEEE Transactions on Cybernetics, 52(10), 10200-10213. https://doi.org/10.1109/TCYB.2021.3069338

Ugurlu, H. I., Pham, X. H. & Kayacan, E. (2022). Sim-to-Real Deep Reinforcement Learning for Safe End-to-End Planning of Aerial Robots. Robotics, 11(5), Article 109. https://doi.org/10.3390/robotics11050109

Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2022). Single-layer vision transformers for more accurate early exits with less overhead. Neural Networks, 153, 461-473. https://doi.org/10.1016/j.neunet.2022.06.038

Gaikwad, N., Liu, L., Griffiths, M. P., Vang, M. Ø., Grombacher, D. & Larsen, J. J. (2022). Thermal Model of the Apsu Transmitter for Lightweight and Compact Heat Sink Design. 11-13. Abstract from The 8th International Workshop on Magnetic Resonance Sounding, Strasbourg, France. https://mrs2021.sciencesconf.org/data/pages/proceedings_MRS2021_distrib_v2.pdf

Besson, M., Alison, J., Bjerge, K., Gorochowski, T. E., Høye, T. T., Jucker, T., Mann, H. M. R. & Clements, C. F. (2022). Towards the fully automated monitoring of ecological communities. Ecology Letters, 25(12), 2753-2775. https://doi.org/10.1111/ele.14123

Hansen, J. G., Heiß, M., Kozłowski, M. & Kayacan, E. (2022). UAV Trajectory Evaluation in Large Industrial Environments: A Cost-Effective Solution. In 2022 European Control Conference (ECC) (pp. 1336-1341). IEEE. https://doi.org/10.23919/ECC55457.2022.9838352

Oleksiienko, I., Tran, D. T. & Iosifidis, A. (2022). Variational Neural Networks implementation in Pytorch and JAX[Formula presented]. Software Impacts, 14, Article 100431. https://doi.org/10.1016/j.simpa.2022.100431

Khare, S. K., Gaikwad, N. & Bajaj, V. (2022). VHERS: A Novel Variational Mode Decomposition and Hilbert Transform-Based EEG Rhythm Separation for Automatic ADHD Detection. IEEE Transactions on Instrumentation and Measurement, 71, 1-10. Article 4008310. https://doi.org/10.1109/TIM.2022.3204076

Khan, T. M., Khan, M. A. U., Rehman, N. U., Naveed, K., Afridi, I. U., Naqvi, S. S. & Raazak, I. (2022). Width-wise vessel bifurcation for improved retinal vessel segmentation. Biomedical Signal Processing and Control, 71(Part A), Article 103169. https://doi.org/10.1016/j.bspc.2021.103169

Tøttrup, D., Skovgaard, S. L., Sejersen, J. L. F. & de Figueiredo, R. P. (2021). A fast and accurate approach to multiple-vehicle localization and tracking from monocular aerial images. Journal of Imaging, 7(12), Article 270. https://doi.org/10.3390/jimaging7120270

Lindahl Petersen , K., Ladegaard Jensen, K., Back Nielsen, M., Pas, L-C., Jensen, N-P., Nielsen, P. R., Bøjer, O. M., Nyholm Jørgensen, R., Laursen, M. S., Teimouri, N. & Hartmann, B. (2021). Analyse af mulige herbicidbesparelser ved brug af erfaringer og data fra RoboWeedMaPS. Datalogisk Institut. https://datalogisk.dk/wp-content/uploads/2021/03/MST_20rapport_version_2_2002092021.pdf

Gislum, R., Thomsen, I. K., Hansen, E. M., Mortensen, A. K., Larsen, R. & Olesen, J. E., (2021). Analyser i pilotprojekt om biomasse på baggrund af data fra forsøgsår 2020, No. 2021-0206943, 18 p., May 05, 2021. Rådgivningsnotat fra DCA – National Center for Fødevarer og Jordbrug

Somerville, G. J., Mathiassen, S. K., Melander, B., Bøjer, O. M. & Nyholm Jørgensen, R. (2021). Analysing the number of images needed to create robust variable spray maps. Precision Agriculture, 22(5), 1377-1396. https://doi.org/10.1007/s11119-021-09800-3

Oleksiienko, I. & Iosifidis, A. (2021). Analysis of voxel-based 3D object detection methods efficiency for real-time embedded systems. In N. Mallenahalli, A. Bhattacharya, S. Senatore, A. Negi & A. Hirose (Eds.), 2021 International Conference on Emerging Techniques in Computational Intelligence (ICETCI) (pp. 59-64). IEEE. https://doi.org/10.1109/ICETCI51973.2021.9574075

Bjerge, K., Nielsen, J. B., Sepstrup, M. V., Helsing-Nielsen, F. & Høye, T. T. (2021). An automated light trap to monitor moths (Lepidoptera) using computer vision-based tracking and deep learning. Sensors (Switzerland), 21(2), Article 343. https://doi.org/10.3390/s21020343

Ahmadi, H., Rafiei Foroushani, M., Afshari-Igder, M., Gheisarnejad Chirani, M. & Khooban, M. H. (2021). An Energy Efficient Solution for Fuel Cell Heat Recovery in Zero-Emission Ferry Boats: Deep Deterministic Policy Gradient. I E E E Transactions on Vehicular Technology, 70(8), 7571-7581. Article 9477203. https://doi.org/10.1109/TVT.2021.3094899.

Magris, M. & Iosifidis, A. (2021). Approximate Bayes factors for unit root testing. Paper presented at International Association for Applied Econometrics Annual Conference 2021, Rotterdam, Netherlands. https://www.researchgate.net/publication/349492007_Approximate_Bayes_factors_for_unit_root_testing

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