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

Kharghanian, R., Peiravi, A., Moradi, F. & Iosifidis, A. (2021). Pain detection using batch normalized discriminant restricted Boltzmann machine layers. Journal of Visual Communication and Image Representation, 76, Article 103062. https://doi.org/10.1016/j.jvcir.2021.103062

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

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. (Producer). (2016). OptiMek Temadag - En fremtid med droner i landbruget. Pictures, Video and sound recordings (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. In Fuzzy Systems (FUZZ-IEEE), 2015 IEEE International Conference on (pp. 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. In Proceedings International Conference of Agricultural Engineering (pp. 1-7) http://www.geyseco.es/geystiona/adjs/comunicaciones/304/C02000001.pdf

Kiranyaz, S., Ince, T., Iosifidis, A. & Gabbouj, M. (2020). Operational neural networks. Neural Computing and Applications, 32(11), 6645-6668. Advance online publication. https://doi.org/10.1007/s00521-020-04780-3

Hansen, E. M., Thomsen, I. K., Cronin, I. V., Gislum, R., Larsen, R. & Mortensen, A. K., (2023). Opdatere trappemodel om dækningsgrad af efterafgrøder ved kontrol i forhold til etableringstidspunkt, No. 2022-0445946, 18 p., Apr 26, 2023. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Heidari, N. & Iosifidis, A. (2021). On the spatial attention in spatio-temporal graph convolutional networks for skeleton-based human action recognition. In IJCNN 2021 - International Joint Conference on Neural Networks, Proceedings IEEE. https://doi.org/10.1109/IJCNN52387.2021.9534440

Magris, M. (2019). On the simulation of the Hawkes process via Lambert-W functions. arXiv. https://arxiv.org/abs/1907.09162

Iosifidis, A., Tefas, A. & Pitas, I. (2013). On the optimal class representation in Linear Discriminant Analysis. IEEE Transactions on Neural Networks and Learning Systems, 24(9), 1491-1497. https://doi.org/10.1109/TNNLS.2013.2258937

Iosifidis, A. & Gabbouj, M. (2015). On the kernel Extreme Learning Machine speedup. Pattern Recognition Letters, 68/1, 205-210. https://doi.org/10.1016/j.patrec.2015.09.015

Iosifidis, A., Tefas, A. & Pitas, I. (2014). On the Kernel Extreme Learning Machine Classifier. Pattern Recognition Letters, 54, 11-17. https://doi.org/10.1016/j.patrec.2014.12.003

Samiee, K., Iosifidis, A. & Gabbouj, M. (2017). On the comparison of random and Hebbian weights for the training of single-hidden layer feedforward neural networks. Expert Systems with Applications, 83, 177-186. https://doi.org/10.1016/j.eswa.2017.04.025

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. In R. John, H. Hagras & O. Castillo (Eds.), Studies in Fuzziness and Soft Computing (Vol. 362, pp. 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. In Proceedings of the 3rd International Conference on Progress in Additive Manufacturing (Pro-AM 2018) (pp. 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. In 2018 Annual American Control Conference, ACC 2018 (pp. 6378-6383). Article 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. In 2019 International Conference on Robotics and Automation, ICRA 2019 (pp. 7727-7733). Article 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

Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). On Feature Diversity in Energy-based models. Paper presented at International Conference on Learning Representations Workshop on Energy-Based Models, , Vienna. https://openreview.net/pdf?id=ks3Q08yy66r

Iosifidis, A., Mygdalis, V., Tefas, A. & Pitas, I. (2016). One-Class Classification based on Extreme Learning and Geometric Class Information. Neural Processing Letters, 45(2), 577-592. https://doi.org/10.1007/s11063-016-9541-y

Mygdalis, V., Iosifidis, A., Tefas, A. & Pitas, I. (2016). One Class Classification applied in Facial Image Analysis. In 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings (pp. 1644-1648). Article 7532637 IEEE. https://doi.org/10.1109/ICIP.2016.7532637

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), Article 1406. https://doi.org/10.3390/s16091406

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

Jørgensen, R. N. & Maagaard, J. (2008). Omni rotational driving and steering wheel. (Patent No. WO2008138346). http://v3.espacenet.com/publicationDetails/biblio?KC=A1&date=20081120&NR=2008138346A1&DB=EPODOC&locale=en_EP&CC=WO&FT=D

Waris, M. A., Iosifidis, A. & Gabbouj, M. (2016). Object Proposals using CNN-based edge filtering. In 2016 23rd International Conference on Pattern Recognition, ICPR 2016 (pp. 627-632). Article 7899704 IEEE. https://doi.org/10.1109/ICPR.2016.7899704

Bjerge, K., Frigaard, C. E. & Karstoft, H. (2023). Object Detection of Small Insects in Time-Lapse Camera Recordings. Sensors, 23(16), Article 7242. https://doi.org/10.3390/s23167242

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

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

Iosifidis, A. & Gabbouj, M. (2016). Nyström-based Approximate Kernel Subspace Learning. Pattern Recognition, 57, 190-197. https://doi.org/10.1016/j.patcog.2016.03.018

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. In CIGR2004, Beijing, China. Collection of Extent Abstracts, Vol. 1, p. I-63. Paper on CD: ISBN 7-80167-707-2/ (pp. 537-537)

Mehndiratta, M. & Kayacan, E. (2016). Numerical Investigation of Gaussian Filters with a Combined Type Bayesian Filter for Nonlinear State Estimation. In IFAC-PapersOnLine (18 ed., Vol. 49, pp. 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. In 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing, MLSP 2021 IEEE. https://doi.org/10.1109/MLSP52302.2021.9596307

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

Larsen, J. J., Dalgaard, E. B. & Auken, E. (2013). Noise Cancelling of Multichannel MRS Signals with a Time Dependent Harmonic Model. Poster session presented at AGU Fall Meeting, San Francisco, United States.

Larsen, J. J., Dalgaard, E. B. & Auken, E. (2013). Noise cancelling of MRS signals combining model-based removal of powerline harmonics and multichannel Wiener filtering. Geophysical Journal International, 196(2), 828-836. https://doi.org/10.1093/gji/ggt422

Dalgaard, E., Auken, E. & Larsen, J. J. (2011). Noise Cancellation of Multichannel Magnetic Resonance Sounding Measurements with Wiener and Adaptive Filters. Abstract from EAGE Near Surface 2011, Leiceister, United Kingdom. http://www.earthdoc.org/publication/publicationdetails/?publication=53995

Eriksen, J., Frandsen, T. S., Knudsen, L., Skovsen, S., Nyholm Jørgensen, R., Steen, K. A., Green, O. & Rasmussen, J. (2019). Nitrogen fertilization of grass-clover leys. In O. Huguenin-Elie, B. Studer, R. Kölliker, D. Reheul, M. Probo, P. Barre, U. Feuerstein, I. Roldan-Ruiz, P. Mariotte & A. Hopkins (Eds.), Improving sown grasslands through breeding and management: Proceedings of the Joint 20th Symposium of the European Grassland Federation and the 33rd Meeting of the EUCARPIA Section "Fodder Crops and Amenity Grasses", Zürich, Switzerland, 24-27 June 2019 (pp. 103-109). Wageningen Academic Publishers.

Kremer, T., Larsen, J. J. & Nguyen, F. (2018). New Processing Schemes for the Removal of Harmonic Noise from SNMR Signals in Complex Multi-Frequency Noise Environments. In 24th European Meeting of Environmental and Engineering Geophysics European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.201802552

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

Kayacan, E., Kayacan, E., Ramon, H. & Saeys, W. (2012). Neuro-Fuzzy Control with a Novel Training Method Based-on Sliding Mode Control Theory: Application to Tractor Dynamics. In IFAC Proceedings Volumes (22 ed., Vol. 45, pp. 889-894). Elsevier. https://doi.org/10.3182/20120905-3-HR-2030.00014

V. Topalev, A., Kayacan, E., Oniz, Y. & Kaynak, O. (2009). Neuro-Fuzzy Control of Antilock Braking System Using Variable-Structure-Systems-based Learning Algorithm. In Adaptive and Intelligent Systems, 2009. ICAIS '09. International Conference on (pp. 166-171). IEEE . https://doi.org/10.1109/ICAIS.2009.35

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Revised 10.08.2023

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