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Institut for Elektro- og Computerteknologi

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

Sortér efter: Dato | Forfatter | Titel

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, Artikel 1293621. https://doi.org/10.3389/fpubh.2024.1293621

Jørgensen, R. & Sørensen, C. A. G. (2005). Præcisionsjordbrug - hvor svært kan det være? I Proc. Plantekongres 2005, Herning Kongrescenter. ISBN 87-984996-6-1 (s. 74-75) https://www.researchgate.net/publication/280306170_Praecisionsjordbrug_-_hvor_svaert_kan_det_vaere

Grombacher, D., Liu, L., Larsen, J. J. & Auken, E. (2018). Practical considerations for small receive coils in surface NMR. Journal of Applied Geophysics, 154, 81-92. https://doi.org/10.1016/j.jappgeo.2018.04.005

Li, L., Looney, D., Park, C., Rehman, N. U. & Mandic, D. P. (2011). Power independent EMG based gesture recognition for robotics. I 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE. https://doi.org/10.1109/iembs.2011.6090036

Grombacher, D. J., Larsen, J. J. & Auken, E. (2016). Potential for Square Wave Transmitters in Surface NMR. I Near Surface Geoscience 2016: 22nd European Meeting of Environmental and Engineering Geophysics (Bind 2016). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.201602008

Christiansen, P., Kragh, M. F., Steen, K. A., Karstoft, H. & Nyholm Jørgensen, R. (2017). Platform for evaluating sensors and human detection in autonomous mowing operations. Precision Agriculture, 18(3), 350-365. https://doi.org/10.1007/s11119-017-9497-6

Dyrmann, M., Karstoft, H. & Midtiby, H. S. (2016). Plant species classification using deep convolutional neural network. Biosystems Engineering, 151(November), 72-80. https://doi.org/10.1016/j.biosystemseng.2016.08.024

Nyholm Jørgensen, R. (2020). Plantekongres 2020 - RoboWeedMaps præsenterer: Flere muligheder med digital ukrudtsgenkendelse. Billeder, Video- og Lydoptagelser (digital) https://www.youtube.com/watch?v=HEsJ9k1SJYM

Camci, E. & Kayacan, E. (2019). Planning swift maneuvers of quadcopter using motion primitives explored by reinforcement learning. I Proceedings of the American Control Conference: 2019 American Control Conference, ACC 2019 (s. 279-285). Artikel 8815352 IEEE.

Dyrmann, M., Mortensen, A. K., Midtiby, H. S. & Nyholm Jørgensen, R. (2016). Pixel-wise classification of weeds and crops in images by using a Fully Convolutional neural network. Afhandling præsenteret på International Conference on Agricultural Engineering 2016, Aarhus, Danmark. http://conferences.au.dk/uploads/tx_powermail/cigr2016paper_semanticsegmentation.pdf

Gislum, R. & Nyholm Jørgensen, R. (2016). Pilotprojekt vedr. billedanalyse på golfbaner med henblik på reduktion i pesticidforbruget og implementering af IPM.

Jun Hao Nicholas, N., Bahadir Kocer, B., Kayacan, E. & Wai Yee, Y. (2015). Piezoceramic Materials for Energy Harvesting on 3D Printed Unmanned Aerial Vehicles: A Feasibility Study. I Humanitarian Technology Conference (R10-HTC), 2015 IEEE Region 10 (s. 1-4). IEEE. https://doi.org/10.1109/R10-HTC.2015.7391845

Ma, X., J. Hegarty, P., Abildgaard Pedersen, J., Johansen, L. G. & Larsen, J. J. (2016). Personal Sound Zones: The significance of loudspeaker driver nonlinear distortion. Afhandling præsenteret på 2016 AES International Conference on Sound Field Control, Guildford, Storbritannien. https://secure.aes.org/forum/pubs/conferences/?elib=18305

Maslim, R., Chaoyi, H., Yixi, Z., Linhao, J., Bahadir Kocer, B. & Kayacan, E. (2015). Performance evaluation of adaptive and nonadaptive fuzzy structures for 4D trajectory tracking of quadrotors: A comparative study. I Fuzzy Systems (FUZZ-IEEE), 2015 IEEE International Conference on (s. 1-7). IEEE. https://doi.org/10.1109/FUZZ-IEEE.2015.7337945

Ferrarini, B., Ehsan, S., Leonardis, A., Rehman, N. U. & McDonald-Maier, K. D. (2018). Performance Characterization of Image Feature Detectors in Relation to the Scene Content Utilizing a Large Image Database. IEEE Access, 6, 8564-8573. https://doi.org/10.1109/access.2018.2795460

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

Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2020). Parallelized Hybrid Bloch Solver for Surface Nuclear Magnetic Resonance. Abstract fra Near Surface Geoscience 2020.

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. I ISR Europe 2023: 56th International Symposium on Robotics, in cooperation with Fraunhofer IPA September 26 – 27, 2023 in Stuttgart (s. 16-21). VDE Verlag GmbH. https://ieeexplore.ieee.org/document/10363048

Dalgaard, E. B., Auken, E. & Larsen, J. J. (2012). Optimized Wiener filtering with the Numis Poly system. Abstract fra Magnetic Resonance in the Subsurface, Hannover, Tyskland.

Kamble, K., Jensen, C. E. H. & Larsen, J. J. (2024). Optimized Suppression of VLF Radio Noise in Time-lapse Transient Electromagnetic Data. Abstract fra AGU Fall meeting 2024, Washington DC, USA.

S. Nadimi, E., Blanes-Vidal, V. & Jørgensen, R. N. (2010). OPTIMIZATION OF ENERGY CONSUMPTION DURING GRAIN DRYING process using wireless sensor networks.

Nyholm Jørgensen, R. (2016). OptiMek Temadag - En fremtid med droner i landbruget. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=vZii3S9QP_s&feature=youtu.be

Ahmadieh Khanesar, M., Kayacan, E. & Kaynak, O. (2015). Optimal Sliding Mode Type-2 TSK Fuzzy Control of a 2-DOF Helicopter. I Fuzzy Systems (FUZZ-IEEE), 2015 IEEE International Conference on (s. 1-6). IEEE . https://doi.org/10.1109/FUZZ-IEEE.2015.7337799

Hassan, S., Ahmadieh Khanesar, M., Kayacan, E., jaafar, J. & Khosravi, A. (2016). Optimal design of adaptive type-2 neuro-fuzzy systems: A review. Applied Soft Computing, 44, 134-143. https://doi.org/10.1016/j.asoc.2016.03.023

Van Beers, R., Gutierrez, L. L., Schenk, A., Nicolai, B., Kayacan, E. & Saeys, W. (2014). Optical measurement techniques for the ripeness determination of Braeburn apples. I Proceedings International Conference of Agricultural Engineering (s. 1-7) http://www.geyseco.es/geystiona/adjs/comunicaciones/304/C02000001.pdf

Madsen, S. L., Mathiassen, S. K., Dyrmann, M., Laursen, M. S., Paz, L.-C. & Nyholm Jørgensen, R. (2020). Open Plant Phenotype Database of Common Weeds in Denmark. Remote Sensing, 12(8), Artikel 1246. https://doi.org/10.3390/rs12081246

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

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

Kayacan, E., Kayacan, E., Chen, I.-M., Ramon, H. & Saeys, W. (2018). On The Comparison of Model-Based and Model-Free Controllers in Guidance, Navigation and Control of Agricultural Vehicles. I R. John, H. Hagras & O. Castillo (red.), Studies in Fuzziness and Soft Computing (Bind 362, s. 49-73). Springer. https://doi.org/10.1007/978-3-319-72892-6_3

Low, J. M., Govdeli, Y., Ravindrababu, S. & Kayacan, E. (2018). ON THE COMPARISON OF DIAMOND HONEYCOMB AND 3D- KAGOME STRUCTURES FOR 3D PRINTED UAVS. I Proceedings of the 3rd International Conference on Progress in Additive Manufacturing (Pro-AM 2018) (s. 341-346) https://doi.org/10.25341/D49G6P

Figueiredo, R. P. D., Hansen, J. G., Le Fevre Sejersen, J., Brandão, M. & Kayacan, E. (2021). On the Advantages of Multiple Stereo Vision Camera Designs for Autonomous Drone Navigation.

Teimouri, N., Omid, M., Mollazade, K., Mousazadeh, H., Alimardani, R. & Karstoft, H. (2018). On-line separation and sorting of chicken portions using a robust vision-based intelligent modelling approach. Biosystems Engineering, 167, 8-20. https://doi.org/10.1016/j.biosystemseng.2017.12.009

Mehndiratta, M. & Kayacan, E. (2018). Online Learning-based Receding Horizon Control of Tilt-rotor Tricopter: A Cascade Implementation. I 2018 Annual American Control Conference, ACC 2018 (s. 6378-6383). Artikel 8430814 IEEE. https://doi.org/10.23919/ACC.2018.8430814

Sarabakha, A. & Kayacan, E. (2019). Online deep learning for improved trajectory tracking of unmanned aerial vehicles using expert knowledge. I 2019 International Conference on Robotics and Automation, ICRA 2019 (s. 7727-7733). Artikel 8794314 IEEE. https://doi.org/10.1109/ICRA.2019.8794314

Sarabakha, A. & Kayacan, E. (2020). Online Deep Fuzzy Learning for Control of Nonlinear Systems Using Expert Knowledge. IEEE Transactions on Fuzzy Systems, 28(7), 1492-1503. https://doi.org/10.1109/TFUZZ.2019.2936787

Sarabakha, A., Qiao, Z., Ramasamy, S. & Suganthan, P. N. (2023). Online Continual Learning for Control of Mobile Robots. I 2023 International Joint Conference on Neural Networks (IJCNN) (s. 1) https://ieeexplore.ieee.org/document/10191188

Fu, C., Duan, R., Kircali, D. & Kayacan, E. (2016). Onboard Robust Visual Tracking for UAVs Using a Reliable Global-Local Object Model. Sensors, 16(9), Artikel 1406. https://doi.org/10.3390/s16091406

Jørgensen, R. N. & Maagaard, J. (2008). Omni rotational driving and steering wheel. (Patentnummer WO2008138346). http://v3.espacenet.com/publicationDetails/biblio?KC=A1&date=20081120&NR=2008138346A1&DB=EPODOC&locale=en_EP&CC=WO&FT=D

Grombacher, D., Griffiths, M. P., Vang, M. Ø., Kass, M. A. & Larsen, J. J. (2024). Observation of spikelets in steady-state surface nuclear magnetic resonance data. Geophysics, 89(2), J1-J8. https://doi.org/10.1190/GEO2023-0145.1

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

Hansen, M. K., Nyholm Jørgensen, R. & Pedersen, H. (2015). Object Detection and Terrain Classification in Agricultural Fields using 3D Lidar Data. I Computer Vision Systems: 10th International Conference, ICVS 2015, Proceedings (Bind 9163, s. 188-197). Springer. https://doi.org/10.1007/978-3-319-20904-3_18

Christensen, L. K. & Jørgensen, R. (2004). Nutrient stress discrimination of N, P, and K deficiencies in barley utilising multi-band reflection at sub-leaf scale. I CIGR2004, Beijing, China. Collection of Extent Abstracts, Vol. 1, p. I-63. Paper on CD: ISBN 7-80167-707-2/ (s. 537) https://www.academia.edu/67063468/Nutrient_stress_discrimination_of_N_P_and_K_deficiencies_in_barley_utilising_multi_band_reflection_at_sub_leaf_scale?uc-g-sw=67063526

Mehndiratta, M. & Kayacan, E. (2016). Numerical Investigation of Gaussian Filters with a Combined Type Bayesian Filter for Nonlinear State Estimation. I IFAC-PapersOnLine (18 udg., Bind 49, s. 446-453). Elsevier. https://doi.org/10.1016/j.ifacol.2016.10.206

Sarabakha, A., Imanberdiyev, N., Kayacan, E., Ahmadieh Khanesar, M. & Hagras, H. (2017). Novel Levenberg-Marquardt Based Learning Algorithm for Unmanned Aerial Vehicles. Information Sciences, 417, 361-380. https://doi.org/10.1016/j.ins.2017.07.020

Dormann, F., Frisk, O., Andersen, L. N. & Pedersen, C. F. (2021). Not All Noise Is Accounted Equally: How Differentially Private Learning Benefits From Large Sampling Rates. I 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing, MLSP 2021 IEEE. https://doi.org/10.1109/MLSP52302.2021.9596307

Hemakom, A., Ahrabian, A., Looney, D., Rehman, N. U. & Mandic, D. P. (2015). Nonuniformly sampled trivariate empirical mode decomposition. I 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) IEEE. https://doi.org/10.1109/icassp.2015.7178660

Kayacan, E., Kayacan, E., Ramon, H. & Saeys, W. (2014). Nonlinear modeling and identification of an autonomous tractor–trailer system. Computers and Electronics in Agriculture, 106, 1-10. https://doi.org/10.1016/j.compag.2014.05.002

Ma, X., Hegarty, P. J., Jørgensen, K. F. & Larsen, J. J. (2019). Nonlinear distortion reduction in sound zones by constraining individual loudspeaker control effort. Journal of the Audio Engineering Society, 67(9), 641-654. https://doi.org/10.17743/jaes.2019.0015

Rubio Hervas, J., Reyhanoglu, M., Tang, H. & Kayacan, E. (2015). Nonlinear control of fixed-wing UAVs in presence of stochastic winds. Communications in Nonlinear Science and Numerical Simulation, 33, 57-69. https://doi.org/10.1016/j.cnsns.2015.08.026

Rasmussen, S., Skovgaard Nyboe, N., Mai, S. & Larsen, J. J. (2017). Noise properties of Fourier deconvolution for time-domain electromagnetic soundings. Geophysics, 82(5), 257-266. https://doi.org/10.1190/geo2016-0588.1

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Revideret 10.08.2023

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AU Engineering