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

Sort by: Date | Author | Title

Larsen, D., Steen, K. A., Skovsen, S., Grooters, K., Eriksen, J., Nyholm Jørgensen, R., Dyrmann, M. & Green, O. (2018). Semantic Segmentation of Clover-Grass Images using Images from Commercially Available Drones. In P. W. G. Groot Koerkamp, C. Lokhorst , A. H. Ipema, C. Kempenaar, C. M. Groenestein, C. G. van Oostrum & N. J. Ros (Eds.), Book of Abstracts of the European Conference on Agricultural Engineering: AgEng2018 (pp. 110). Wageningen University. https://doi.org/10.18174/471678

Cavagna, A., Li, N., Iosifidis, A. & Zhang, Q. (2023). Semantic Communication Enabling Robust Edge Intelligence for Time-Critical IoT Applications. In 2023 IEEE International Conference on Communications Workshops (ICC Workshops) (pp. 1617-1622). IEEE. https://doi.org/10.1109/ICCWorkshops57953.2023.10283786

Chen, Q., Chen, J., Lang, X., Xie, L., Rehman, N. U. & Su, H. (2021). Self-tuning variational mode decomposition. Journal of the Franklin Institute, 358(15), 7825-7862. https://doi.org/10.1016/j.jfranklin.2021.07.021

Hansen, M. K., Underwood, J. & Karstoft, H. (2016). Self-supervised Traversability Assessment in Field Environments with Lidar and Camera. Poster session presented at International Conference on Agricultural Engineering 2016, Aarhus, Denmark.

Kiranyaz, S., Malik, J., Abdallah, H. B., Ince, T., Iosifidis, A. & Gabbouj, M. (2021). Self-organized Operational Neural Networks with Generative Neurons. Neural Networks, 140, 294-308. https://doi.org/10.1016/j.neunet.2021.02.028

Zahra, A., Kanwal, N., Rehman, N. U., Ehsan, S. & McDonald-Maier, K. D. (2017). Seizure detection from EEG signals using Multivariate Empirical Mode Decomposition. Computers in Biology and Medicine, 88, 132-141. https://doi.org/10.1016/j.compbiomed.2017.07.010

Tu, G. J., Karstoft, H., Pedersen, L. J. & Jørgensen, E. (2014). Segmentation of sows in farrowing pens. IET Image Processing, 8(1), 56-68. https://doi.org/10.1049/iet-ipr.2012.0734

Mortensen, A. K., Bender, A., Whelan, B., Barbour, M. M., Sukkarieh, S., Karstoft, H. & Gislum, R. (2018). Segmentation of lettuce in coloured 3D point clouds for fresh weight estimation. Computers and Electronics in Agriculture, 154, 373-381. https://doi.org/10.1016/j.compag.2018.09.010

Giselsson, T. M., Midtiby, H. & Jørgensen, R. N. (2013). Seedling Discrimination with Shape Features Derived from a Distance Transform. Sensors, 13(5), 5585-5602. https://doi.org/10.3390/s130505585

Iosifidis, A. & Gabbouj, M. (2016). Scaling up Class-Specific Kernel Discriminant Analysis for large-scale Face Verification. IEEE Transactions on Information Forensics and Security, 11(11), 2453-2465. Article 7494969. https://doi.org/10.1109/TIFS.2016.2582562

Sveistrup, D., Jørgensen, R. N., Green, O., Nørremark, M. & Sørensen, C. A. G. (2010). Satellite, Internet & Computer Aided Trails.

Thanh Tran, D., Waris, M. A., Gabbouj, M. & Iosifidis, A. (2017). Sample-based regularization for Support Vector Machine Classification. In The 7th International Conference on Image Processing, Tools and Applications http://www.cs.tut.fi/~iosifidi/files/conference/2017_IPTA_DropOutSVM.pdf?dl=0

Aytekin, C., Iosifidis, A., Kiranyaz, S. & Gabbouj, M. (2016). Salient Object Segmentation based on Linearly Combined Affinity Graphs. In 2016 23rd International Conference on Pattern Recognition, ICPR 2016 (pp. 3769-3774). Article 7900221 IEEE. https://doi.org/10.1109/ICPR.2016.7900221

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

le Fevre Sejersen, J., Pimentel De Figueiredo, R. & Kayacan, E. (2021). Safe Vessel Navigation Visually Aided by Autonomous Unmanned Aerial Vehicles in Congested Harbors and Waterways. In 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) (pp. 1901-1907) https://doi.org/10.1109/CASE49439.2021.9551637

Dong, Y., Fu, C. & Kayacan, E. (2016). RRT-based 3D Path Planning for Formation Landing of Quadrotor. In 2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016 (pp. 1-6). Article 7838567 IEEE . https://doi.org/10.1109/ICARCV.2016.7838567

Sørensen, R. A., Nielsen, M. & Karstoft, H. (2020). Routing in congested baggage handling systems using deep reinforcement learning. Integrated Computer-Aided Engineering, 27(2), 139-152. https://doi.org/10.3233/ICA-190613

Sveistrup, D., Jørgensen, R. N., Nørremark, M., Green, O., Sørensen, C. A. G. & S. Nadimi, E. (2010). RoPDeF - semi-automated and web-based Route Plan Designer of full-scale Field trials for tractor guidance systems. In Conference on Precision Crop Protection (Vol. 3). http://www.precision-crop-protection.uni-bonn.de/gk_conference/abstracts_2010.pdf

Kayacan, E., Kayacan, E., Ramon, H. & Saeys, W. (2014). Robust Tube-based Decentralized Nonlinear Model Predictive Control of an Autonomous Tractor-Trailer System. IEEE - ASME Transactions on Mechatronics, 20(1), 447-456. https://doi.org/10.1109/TMECH.2014.2334612

Mehndiratta, M., Kayacan, E., Reyhanoglu, M. & Kayacan, E. (2020). Robust Tracking Control of Aerial Robots Via a Simple Learning Strategy-Based Feedback Linearization. IEEE Access, 8, 1653-1669. https://doi.org/10.1109/ACCESS.2019.2962512

Khalid, S. S., Rehman, N. U. & Abrar, S. (2017). Robust stochastic integration filtering for nonlinear systems under multivariate t -distributed uncertainties. Signal Processing, 140, 53-59. https://doi.org/10.1016/j.sigpro.2017.05.007

Skovsen, S. K., Laursen, M. S., Kristensen, R. K., Rasmussen, J., Dyrmann, M., Eriksen, J., Gislum, R., Nyholm Jørgensen, R. & Karstoft, H. (2021). Robust Species Distribution Mapping of Crop Mixtures Using Color Images and Convolutional Neural Networks. Sensors, 21( 1), Article 175. https://doi.org/10.3390/s21010175

Iqbal, S., Naveed, K., Naqvi, S. S., Naveed, A. & Khan, T. M. (2023). Robust retinal blood vessel segmentation using a patch-based statistical adaptive multi-scale line detector. Digital Signal Processing: A Review Journal, 139, Article 104075. https://doi.org/10.1016/j.dsp.2023.104075

Passalis, N., Iosifidis, A., Gabbouj, M. & Tefas, A. (2021). Robust hypersphere-based weight imprinting for few-shot learning. In 2020 28th European Signal Processing Conference (EUSIPCO (pp. 1392-1396). Article 9287340 IEEE. https://doi.org/10.23919/Eusipco47968.2020.9287340

Chumachenko, K., Iosifidis, A. & Gabbouj, M. (2021). Robust fast subclass discriminant analysis. In 2020 28th European Signal Processing Conference (EUSIPCO) (pp. 1397-1401). Article 9287557 IEEE. https://doi.org/10.23919/Eusipco47968.2020.9287557

Laakom, F., Raitoharju, J., Nikkanen, J., Iosifidis, A. & Gabbouj, M. (2021). Robust channel-wise illumination estimation. In 32rd British Machine Vision Conference https://arxiv.org/pdf/2111.05681.pdf

Rasmussen, S., Nyboe, N. S., Mai, S. & Larsen, J. J. (2018). Robust cancellation of minimum shift keying-encoded radio interference in data from the transient electromagnetic method. Geophysics, 83(2), E87-E94. https://doi.org/10.1190/GEO2017-0611.1

Khalid, S. S., Rehman, N. U., Abrar, S. & Mihaylova, L. (2018). Robust Bayesian Filtering Using Bayesian Model Averaging and Restricted Variational Bayes. In 2018 21st International Conference on Information Fusion (FUSION) IEEE. https://doi.org/10.23919/icif.2018.8455608

Nyholm Jørgensen, R., Madsen, S. L. & Laursen, M. S. (2016). RoboWeedSupport - Weed Mapping with drones using a DJI Matrice 100 with a Velodyne Lidar.. Pictures, Video and sound recordings (digital), YouTube. https://www.youtube.com/watch?v=91LaKHiHiDw

Laursen, M. S., Nyholm Jørgensen, R., Dyrmann, M. & Poulsen, R. (2017). RoboWeedSupport: Sub Millimeter Weed Image Acquisition in Cereal Crops with Speeds up till 50 Km/h. World Academy of Science, Engineering and Technology. Proceedings, 4(4), 1391. https://www.waset.org/abstracts?q=Mads%20Dyrmann

Laursen, M. S., Nyholm Jørgensen, R., Dyrmann, M. & Poulsen, R. (2017). RoboWeedSupport - Sub Millimeter Weed Image Acquisition in Cereal Crops with Speeds up till 50 Km/h. International Journal of Agricultural and Biosystems Engineering, 11(4), 311-315. http://waset.org/publications/10007027/roboweedsupport-sub-millimeter-weed-image-acquisition-in-cereal-crops-with-speeds-up-till-50-km-h

Madsen, S. L., Laursen, M. S., Poulsen, R. N. & Nyholm Jørgensen, R. (2017). RoboWeedSupport: Semi-automated Unmanned Aerial System for Cost Efficient High Resolution in Sub-millimeter Scale Acquisition of Weed Images. In 19th International Conference on Precision Agriculture: ICPA 2017

Nielsen, P. R., Jensen, N.-P., Dyrmann, M., Nielsen, P.-H. & Nyholm Jørgensen, R. (2017). RoboWeedSupport - Presentation of a cloud based system bridging the gap between in-field weed inspections and decision support systems. Advances in Animal Biosciences, 8(2), 860-864. https://doi.org/10.1017/S2040470017001054

Nyholm Jørgensen, R. (2016). RoboWeedSupport Præsentation og status ano 02SEP2016. Pictures, Video and sound recordings (digital) https://youtu.be/tiGtGArXOHw

Dyrmann, M. & Nyholm Jørgensen, R. (2015). RoboWeedSupport: Weed recognition for reduction of herbicide consumption. In J. V. Stafford (Ed.), Precision agriculture '15: Papers presented at the 10th European Conference on Precision Agriculture Volcani Center, Israel 12-16 July 2015 (pp. 571-578). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-814-8_71, https://doi.org/10.3920/978-90-8686-814-8

Nyholm Jørgensen, R. (2019). RoboWeedMaps - Walking the weed maps with your mobile phone. Pictures, Video and sound recordings (digital), YouTube. https://www.youtube.com/watch?v=9rKahKe_a5c&t=108s

Nyholm Jørgensen, R. (2019). RoboWeedMaps præsenterer pletsprøjtning på FutureCropping demodag den 9 oktober 2019. Pictures, Video and sound recordings (digital), YouTube. https://www.youtube.com/watch?v=YKCR-hARLS8&feature=youtu.be

Nyholm Jørgensen, R. & Laursen, M. S. (2017). RoboWeedMaPS - First Grass-weed field inspection in Winter Wheat using DJI Goggles. Pictures, Video and sound recordings (digital), YouTube. https://www.youtube.com/watch?v=Yma1Psi9OEw

Nyholm Jørgensen, R. & Madsen, S. L. (2017). RoboWeedMaPS - First Automated Weed Mapping test flight with DJI Phantom 4 Pro. Pictures, Video and sound recordings (digital), YouTube. https://www.youtube.com/watch?v=-dHMbt9rwak

Nyholm Jørgensen, R., Nielsen, E. D. & Madsen, S. L. (2017). RoboWeedMaPS - Demo DroneApp beta med DJI Phantom 4. Pictures, Video and sound recordings (digital), YouTube. https://www.youtube.com/watch?v=PQ6sSIk7-0s

Nyholm Jørgensen, R., Laursen, M. S., Teimouri, N., Madsen, S. L., Dyrmann, M., Somerville, G. J. & Mathiassen, S. K. (2019). RoboWeedMaps - Automated weed detection and mapping - Invited talk at SSWM 2019, SDU, Odense Denmark. Pictures, Video and sound recordings (digital), YouTube.

Bochtis, D., Sørensen, C. A. G., Jørgensen, R. N., Nørremark, M., Hameed, I. A. & Swain, K. C. (2011). Robotic weed monitoring. Acta Agriculturae Scandinavica, Section B - Soil & Plant Science, 61(3), 202-208. https://doi.org/10.1080/09064711003796428

Christensen, S., Søgaard, H. T., Jørgensen, R. & Bak, T. (2003). Robotic weeding and automated weed measurements. In DJF rapport (Vol. 88, pp. 161-172). Aarhus Universitet, Det Jordbrugsvidenskabelige Fakultet.

Christiansen, M. P., Larsen, P. G. & Nyholm Jørgensen, R. (2015). Robotic Design Choice Overview using Co-simulation and Design Space Exploration. Robotics, 4, 398-421. https://doi.org/10.3390/robotics4040398

Christiansen, M. P., Larsen, P. G. & Nyholm Jørgensen, R. (2014). Robotic design choice overview using co-simulation. Abstract from Agromek and NJF joint seminar, Herning, Denmark.

Ravelo, B., Miranda, J., Cabral, J., Wagner, S. R., Pedersen, C. F., Memon, M., Mathiesen, M. & Lalléchère, S. (2015). RF and EMC Investigation on CRIP System for the E-Healthcare CareStore Platform. In 9th European Conference on Antennas and Propagation (EuCAP) 2015 IEEE. http://ieeexplore.ieee.org.ez.statsbiblioteket.dk:2048/xpl/articleDetails.jsp?arnumber=7228157&newsearch=true&queryText=ravelo%20emc%20rf

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

Chumachenko, K., Laakom, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). Rethinking compactness in deep neural networks. Paper presented at International Conference on Machine Learning Workshop on Overparameterization. https://drive.google.com/file/d/1pu5xJMPvKuGFeVCcylEvLz00uLK3UN9I/view

Iosifidis, A., Tefas, A. & Pitas, I. (2013). Representative Class Vector Clustering based Discriminant Analysis. In Intelligent Information Hiding and Multimedia Signal Processing, 2013 Ninth International Conference on (pp. 526-529). IEEE. https://doi.org/10.1109/IIH-MSP.2013.136

Pedersen, C. F., Jensen, J. J., Dalsgaard, P., Larsen, L. B., Saugstrup, D. & Kaldanis, V. (2004). Report on set-up of field-trial. (1. udgave ed.). Information Society Technologies, 507102, My Personal Adaptive Global NET (MAGNET)

Displaying results 201 to 250 out of 1100

Back to the main page

Revised 10.08.2023

AU Engineering