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

Alvarez Tunon, O., Jardón, A. & Balaguer, C. (2017). Plataformas robóticas para la inspección de los pozos de las minas de carbón en las secciones inundadas y no inundadas. I Jornadas Nacionales de Robótica Spansk Robotics Conference

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.

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

Zehtabiyan-Rezaie, N., Iosifidis, A. & Abkar, M. (2023). Physics-Guided Machine Learning for Wind-Farm Power Prediction: Toward Interpretability and Generalizability. PRX Energy, 2(1), Artikel 013009. https://doi.org/10.1103/PRXEnergy.2.013009

Iosifidis, A., Tefas, A. & Pitas, I. (2011). Person Specific Activity Recognition using Fuzzy Learning and Discriminant Analysis. I Signal Processing Conference, 2011 19th European (s. 1974-1978). IEEE. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7074111

Iosifidis, A., Tefas, A. & Pitas, I. (2013). Person Identification from Actions based on Dynemes and Discriminant Learning. I Biometrics and Forensics (IWBF), 2013 International Workshop on IEEE. https://doi.org/10.1109/IWBF.2013.6547320

Iosifidis, A., Tefas, A. & Pitas, I. (2013). Person Identification from Actions based on Artificial Neural Networks. I Computational Intelligence in Biometrics and Identity Management (CIBIM), 2013 IEEE Workshop on (s. 7-13). IEEE. https://doi.org/10.1109/CIBIM.2013.6607907

Ivasic-Kos, M., Iosifidis, A., Tefas, A. & Pitas, I. (2014). Person De-identification in Activity Videos. I Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2014 37th International Convention on (s. 1294-1299). IEEE. https://doi.org/10.1109/MIPRO.2014.6859767

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

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2020). Performance Indicator in Multilinear Compressive Learning. I 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (s. 1822-1828). Artikel 9308418 IEEE. https://doi.org/10.1109/SSCI47803.2020.9308418

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

Angelov, P., Bernardi, M. L., Nardini, F. M., Pecori, R., Valerio, L., Dini, P., Ashraf, S., Aversano, L., Bianchini, M., Brutti, A., Bukovsky, I., Cagnoni, S., Cao, J., Cimitile, M., Dazzi, P., Iammarino, M., Iosifidis, A., Michahelles, F., Mora, A. ... Welsh, M. (2024). PerconAI 2024: 3rd Workshop on Pervasive and Resource-Constrained Artificial Intelligence - Welcome and Committees. I 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (s. 34-35). IEEE. https://doi.org/10.1109/PerComWorkshops59983.2024.10503466

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.

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, Artikel 103062. https://doi.org/10.1016/j.jvcir.2021.103062

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.

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

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

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

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

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. 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

Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). On Feature Diversity in Energy-based models. Afhandling præsenteret på 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. I 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings (s. 1644-1648). Artikel 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), 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

Waris, M. A., Iosifidis, A. & Gabbouj, M. (2016). Object Proposals using CNN-based edge filtering. I 2016 23rd International Conference on Pattern Recognition, ICPR 2016 (s. 627-632). Artikel 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), Artikel 7242. https://doi.org/10.3390/s23167242

Chumachenko, K., Gabbouj, M. & Iosifidis, A. (2022). Object detection and tracking. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition (s. 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. 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

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

Viser resultater 301 til 350 ud af 965

Forrige

Næste

Back to the main page

Revideret 10.08.2023

AU Engineering