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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Green, O., Lindstrøm, J. & Jørgensen, R. N. (2010). Køreskader og påvirkning af udbyttet i kløvergræs. I Plantekongres 2008 (s. 36-38). Aarhus Universitet, Det Jordbrugsvidenskabelige Fakultet.

Simonsen, O. H., Karstoft, H., Kappel, S. L., Hermann, D., Rathleff, M. S. & Ahrendt, P. (2013). Stretch Sensor Device. (Patentnummer PCT/DK2012/050341, WO2013041101). http://worldwide.espacenet.com/publicationDetails/biblio?CC=WO&NR=2013041101A1&KC=A1&FT=D&ND=3&date=20130328&DB=EPODOC&locale=dk_DK

Mademlis, I., Iosifidis, A., Tefas, A. & Pitas, I. (2014). Stereoscopic Video Description for Human Action Recognition. I Computational Intelligence for Multimedia, Signal and Vision Processing (CIMSIVP), 2014 IEEE Symposium on IEEE. https://doi.org/10.1109/CIMSIVP.2014.7013263

Suvei, S.-D., Bodenhagen, L., Kiforenko, L., Christiansen, P., Nyholm Jørgensen, R., Buch, A. G. & Krüger, N. (2016). Stereo and active-sensor data fusion for improved stereo block matching. I A. Campilho, A. Campilho & F. Karray (red.), Image Analysis and Recognition - 13th International Conference, ICIAR 2016, Proceedings: Proceedings of 13th International Conference ICIAR in Memory of Mohamed Kamel (Bind 9730, s. 451-461). Springer. https://doi.org/10.1007/978-3-319-41501-7_51

Grombacher, D., Liu, L., Griffiths, M. P., Vang, M. & Larsen, J. J. (2021). Steady-State Surface NMR for Mapping of Groundwater. Geophysical Research Letters, 48(23), Artikel e2021GL095381. https://doi.org/10.1029/2021GL095381

Laursen, M. S., Midtiby, H. S., Kruger, N. & Jorgensen, R. N. (2014). Statistics-based segmentation using a continuous-scale naive Bayes approach. Computers and Electronics in Agriculture, 109, 271-277. https://doi.org/10.1016/j.compag.2014.10.009

Kayacan, E., Ahmadieh Khanesar, M. & Kayacan, E. (2015). Stabilization of Type-2 Fuzzy Takagi- Sugeno-Kang Identifier Using Lyapunov Functions. I Fuzzy Systems (FUZZ-IEEE), 2015 IEEE International Conference on (s. 1-6). IEEE . https://doi.org/10.1109/FUZZ-IEEE.2015.7337809

Laursen, M. S., Midtiby, H., Krüger, N. & Jørgensen, R. N. (2012). Spray boom for selectively spraying a herbicidal composition onto dicots. (Patentnummer WO 2012/122988 A1).

Chumachenko, K., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2021). Speed-up and Multi-view Extensions to Subclass Discriminant Analysis. Pattern Recognition, 111, Artikel 107660. https://doi.org/10.1016/j.patcog.2020.107660

Soltanian, M., Malik, J., Raitoharju, J., Iosifidis, A., Kiranyaz, S. & Gabbouj, M. (2021). Speech Command Recognition in Computationally Constrained Environments with a Quadratic Self-Organized Operational Layer. I 2021 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN52387.2021.9534232

Jørgensen, R., Christensen, L. K. & Bro, R. (2007). Spectral reflectance at sub-leaf scale including the spatial distribution discriminating NPK stress characteristics in barley using multiway partial least squares regression. International Journal of Remote Sensing, 28(5), 943-962. https://doi.org/10.1080/01431160600735657

Christensen, L. K. & Jørgensen, R. (2004). Spectral NPK stress discrimination in barley plants by use of three wavebands. I Proc. 4th int. Crop Science Congress, Brisbane, Queensland, Australia. Handbook and Abstracts, Section 2.5.3., p. 195. http://www.regional.org.au/au/cs/2004/index.htm

Hansen, O. L. P., Svenning, J. C., Olsen, K., Dupont, S., Garner, B. H., Iosifidis, A., Price, B. W. & Høye, T. T. (2020). Species-level image classification with convolutional neural network enables insect identification from habitus images. Ecology and Evolution, 10(2), 737-747. https://doi.org/10.1002/ece3.5921

Skovsen, S., Laursen, M. S., Gislum, R., Eriksen, J., Dyrmann, M., Mortensen, A. K., Farkhani, S., Karstoft, H., Jensen, N.-P. & Nyholm Jørgensen, R. (2019). Species distribution mapping of grass clover leys using images for targeted nitrogen fertilization. I J. V. Stafford (red.), Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019 (s. 639-645). Wageningen Academic Publishers. https://doi.org/10.3920/978-90-8686-888-9_79

Rydahl, P., Bojer, O. M., Jorgensen, R. N., Dyrmann, M., Andersen, P., Jensen, N. & Sorensen, M. (2018). Spatial variability of optimized herbicide mixtures and dosages. I Proceedings 14th International Conference on Precision Agriculture (ICPA2018) (s. 1-14). Artikel 5040 International Society of Precision Agriculture. https://www.ispag.org/proceedings/?action=abstractid=5040

Christensen, L. K. & Jørgensen, R. (2003). Spatial reflectance at sub-leaf scale discriminating NPK stress in barley. I Proc. 4th ECPA and 1st ECPLF, Berlin, Germany (s. 622-622). Wageningen Academic Publishers.

Christensen, L. K. & Jørgensen, R. (2003). Spatial Reflectance at Sub-Leaf Scale Discriminating NPK Stress Characteristics in Barley Using Multiway Partial Least Squares Regression. Afhandling præsenteret på ASAE Annual International Meeting, Las Vegas, USA. http://asae.frymulti.com/request.asp?JID=5&AID=13744&CID=lnv2003&T=2

Farkhani, S., Kragh, M. F., Christiansen, P. H., Nyholm Jørgensen, R. & Karstoft, H. (2019). Sparse-to-Dense Depth Completion in Precision Farming. I Proceedings of the 3rd International Conference on Vision, Image and Signal Processing, ICVISP 2019: Proceedings of the 3rd International Conference on Vision, Image and Signal Processing Artikel 35 Association for Computing Machinery. https://doi.org/10.1145/3387168.3387230

Pedersen, C. F. & Bäckström, T. (2014). Sparse Time-Frequency Representation of Speech by the Vandermonde Transform. I Proceedings of the Annual Conference of the International Speech Communication Association: INTERSPEECH 2014 (s. 2248-2252)

Iosifidis, A., Tefas, A. & Pitas, I. (2015). Sparse Extreme Learning Machine classifier exploiting Intrinsic Graphs. Pattern Recognition Letters, 65, 192-196. https://doi.org/10.1016/j.patrec.2015.07.036

Jensen, T., Munkholm, L. J., Green , O. & Karstoft, H. (2015). Soil Surface Roughness Using Cumulated Gaussian Curvature. I L. Nalpantidis, V. Krüger, J.-O. Eklundh & A. Gasteratos (red.), Computer Vision Systems : 10th International Conference, ICVS 2015, Proceedings (s. 533-541). Springer. https://doi.org/10.1007/978-3-319-20904-3_48

Vang, M., Grombacher, D., Larsen, J. J. & Wilson, S. (2023). Small coil surface nuclear magnetic resonance in dynamic river systems in New Zealand. I 2nd Conference on Hydrogeophysics 2023, Held at Near Surface Geoscience Conference and Exhibition 2023, NSG 2023 European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202320070

Vang, M., Grombacher, D., Larsen, J. J. & Wilson, S. (2023). SMALL COIL SURFACE NUCLEAR MAGNETIC RESONANCE FOR SHALLOW RESOLUTION OF RIVERS IN NEW ZEALAND. Proceedings of the Symposium on the Application of Geophyics to Engineering and Environmental Problems, SAGEEP, 2023-April.

Ahmadieh Khanesar, M., Kayacan, E., Kaynak, O. & Saeys, W. (2013). Sliding Mode Type-2 Fuzzy Control of Robotic Arm Using Ellipsoidal Membership Functions. I Control Conference (ASCC), 2013 9th Asian (s. 1-6). IEEE. https://doi.org/10.1109/ASCC.2013.6606393

Kayacan, E. & Kaynak, O. (2012). Sliding Mode Control Theory-based Algorithm for Online Learning in Type-2 Fuzzy Neural Networks: Application to Velocity Control of an Electro Hydraulic Servo System. INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 26(7), 645-659. https://doi.org/10.1002/acs.1292

Rubio Hervas, J., Kayacan, E., Reyhanoglu, M. & Tang, H. (2014). Sliding Mode Control of Fixed- Wing UAVs in Windy Environments. I Control Automation Robotics & Vision (ICARCV), 2014 13th International Conference on (s. 986-991). IEEE . https://doi.org/10.1109/ICARCV.2014.7064440

Kayacan, E., Cigdem, O. & Kaynak, O. (2011). Sliding Mode Control Approach for Online Learning as Applied to Type-2 Fuzzy Neural Networks and its Experimental Evaluation. IEEE Transactions on Industrial Electronics, 59(9), 3510-3520. https://doi.org/10.1109/TIE.2011.2182017

Lati, R. N., Rasmussen, J., Andujar, D., Dorado, J., Berge, T. W., Wellhausen, C., Pflanz, M., Nordmeyer, H., Schirrmann, M., Eizenberg, H., Neve, P., Jørgensen, R. N. & Christensen, S. (2021). Site-specific weed management—constraints and opportunities for the weed research community: Insights from a workshop. Weed Research, 61(3), 147-153. https://doi.org/10.1111/wre.12469

Kayacan, E. & Kaynak, O. (2011). Single-step Ahead Prediction Based on the Principle of Concatenation Using Grey Predictors. Expert Systems with Applications, 38(8), 9499-9505. https://doi.org/10.1016/j.eswa.2011.01.143

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

Iosifidis, A., Tefas, A. & Pitas, I. (2015). Single-hidden Layer Feedforward Neural network training using class geometric information. I Lecture Notes: Studies in Computational Intelligence Springer.

Letafat, A., Rafiei Foroushani, M., Sheikh, M., Afshari-Igder, M., Banaei, M., Boudjadar, J. & Khooban, M. H. (2020). Simultaneous energy management and optimal components sizing of a zero-emission ferry boat. Journal of Energy Storage, 28, Artikel 101215. https://doi.org/10.1016/j.est.2020.101215

Cros, O., Volden, M., Flaaris, J. J., Brix, L. C., Pedersen, C. F., Hansen, K. V., Larsen, O. V., Østergaard, L. R. & Haase, J. (2002). Simulating the puncture of the human ventricle. I 10th Annual Medicine Meets Virtual Reality (MMVR) Conference, Digital upgrades: Applying Moore's Law to health

Oniz, Y., Kayacan, E. & Kaynak, O. (2008). Simulated and Experimental Study of Antilock Braking System Using Grey Sliding Mode Control. I Systems, Man and Cybernetics, 2007. ISIC. IEEE International Conference on (s. 90-95). IEEE . https://doi.org/10.1109/ICSMC.2007.4413975

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), Artikel 109. https://doi.org/10.3390/robotics11050109

Fu, C., Sarabakha, A., Kayacan, E., Wagner, C., John, R. & Garibaldi, J. M. (2017). Similarity-based Non-Singleton Fuzzy Logic Control for Improved Uncertainty Handling in Quadrotor UAVs. I Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on (s. 1-6). IEEE. https://doi.org/10.1109/FUZZ-IEEE.2017.8015440

Nielsen, L., Olesen, C. R., Nyholm Jørgensen, R. & Fris, H. J. (2015). Sikring af levesteder på engarealer med biomassehøst i kombination med vildthensyn. Poster session præsenteret på Biodiversitetssymposiet 2015, Aarhus , Danmark.

Nielsen, L., Olesen, C. R., Nyholm Jørgensen, R. & Fris, H. J. (2015). Sikring af levesteder på engarealer med biomassehøst i kombination med vildthensyn. Abstract fra Biodiversitetssymposiet 2015, Aarhus , Danmark.

Liu, L., Grombacher, D., Griffiths, M., Vang, M. & Larsen, J. J. (2023). Signal Processing Steady-State Surface NMR Data. IEEE Transactions on Instrumentation and Measurement, 72, Artikel 6502313. https://doi.org/10.1109/TIM.2023.3264033

Naveed, K., Shaukat, B. & Rehman, N. U. (2017). Signal denoising based on dual tree complex wavelet transform and goodness of fit test. I 2017 22nd International Conference on Digital Signal Processing (DSP) IEEE. https://doi.org/10.1109/icdsp.2017.8096067

Larsen, J. J. & Vienne, G. (2004). Side pumping of double-clad photonic crystal fibers. Optics Letters, 29(5), 436-438. https://doi.org/10.1364/OL.29.000436

Pedersen, C. F., Andersen, O. & Dalsgaard, P. (2010). Separation of Mixed Phase Signals by Zeros of the Z-transform: A Reformulation of Complex Cepstrum Based Separation by Causality. I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings, 2010(35), 5050-5053. https://doi.org/10.1109/ICASSP.2010.5495060

Skjødt, P., Hansen, P. M., Jørgensen, R. & Nielsen, N. E. (2003). Sensor based nitrogen fertilization in winter wheat levelling out spatial variability in protein content. I Proc. 4th ECPA and 1st ECPLF, Berlin, Germany (s. 311-311). Wageningen Academic Publishers.

Skjødt, P. & Jørgensen, R. (2003). Sensor based nitrogen fertilization increasing grain protein yield in winter wheat. Risø Report Bind Risø-R-1389(EN)

Streibig, J. C., Rasmussen, J., Andujar, D., Andreasen, C., Berge, T. W., Chachalis, D., Dittmann, T., Gerhards, R., Giselsson, T. M., Hamouz, P., Jaeger-Hansen, C., Jensen, K., Nyholm Jørgensen, R., Keller, M., Laursen, M., Midtiby, H. S., Nielsen, J., Müller, S., Nordmeyer, H. ... Christensen, S. (2014). Sensor-based assessment of herbicide effects. Weed Research, 54(3), 223–233. https://doi.org/10.1111/wre.12079

Christensen, S., Dyrmann, M., Nyholm Jørgensen, R. & Laursen, M. S. (2021). Sensing for Weed Detection. I Sensing Approaches for Precision Agriculture (s. 275-300). Springer. https://doi.org/10.1007/978-3-030-78431-7, https://doi.org/10.1007/978-3-030-78431-7_10

Gomes, C., Lucani Rötter, D. E., Iosifidis, A., Feng, H., Ejersbo, H. & Frasheri, M. (2024). Sensing and Communication of Data from the Physical Twin. I J. Fitzgerald, C. Gomes & P. G. Larsen (red.), The Engineering of Digital Twins (s. 147-171). Springer. https://doi.org/10.1007/978-3-031-66719-0_7#citeas

Mygdalis, V., Iosifidis, A., Tefas, A. & Pitas, I. (2018). Semi-Supervised Subclass Support Vector Data Description for Image and Video Classification. Neurocomputing, 278, 51-61. https://doi.org/10.1016/j.neucom.2017.08.028

Iosifidis, A., Tefas, A. & Pitas, I. (2014). Semi-supervised classification of human actions based on Neural Networks. I Pattern Recognition (ICPR), 2014 22nd International Conference on (s. 1336-1341). IEEE. https://doi.org/10.1109/ICPR.2014.239

Mortensen, A. K., Dyrmann, M., Karstoft, H., Nyholm Jørgensen, R. & Gislum, R. (2016). Semantic Segmentation of Mixed Crops using Deep Convolutional Neural Network. Afhandling præsenteret på CIGR 2016, World Congress. http://conferences.au.dk/uploads/tx_powermail/biomap_-_cigr_2016_-_paper_-_final.pdf

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Revideret 10.08.2023

AU Engineering