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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Ärje, J., Kärkkäinen, S., Meissner, K., Iosifidis, A., Ince, T., Gabbouj, M. & Kiranyaz, S. (2016). The effect of automated taxa identification errors on biological indices. Expert Systems with Applications, 72, 108-120. https://doi.org/10.1016/j.eswa.2016.12.015

Ärje, J., Milioris, D., Tran, D. T., Jepsen, J. U., Raitoharju, J., Gabbouj, M., Iosifidis, A. & Høye, T. T. (2019). Automatic Flower Detection and Classification System Uing a Light-Weight Convolutional Neural Network. I 27th European Signal Processing Conference EUSIPCO 2019 IEEE. Proceedings of the European Signal Processing Conference http://eusipco2019.org/Proceedings/papertitles.html

Ärje, J., Raitoharju, J., Iosifidis, A., Tirronen, V., Meissner, K., Gabbouj, M., Kiranyaz, S. & Kärkkäinen, S. (2020). Human experts vs. machines in taxa recognition. Signal Processing: Image Communication, 87, [115917]. https://doi.org/10.1016/j.image.2020.115917

Ärje, J., Melvad, C., Jeppesen, M. R., Madsen, S. A., Raitoharju, J., Rasmussen, M. S., Iosifidis, A., Tirronen, V., Gabbouj, M., Meissner, K. & Høye, T. T. (2020). Automatic image-based identification and biomass estimation of invertebrates. Methods in Ecology and Evolution, 11(8), 922-931. https://doi.org/10.1111/2041-210X.13428

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. I 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE) (s. 1901-1907) https://doi.org/10.1109/CASE49439.2021.9551637

baran, E. A., Zhakypov, Z., Kayacan, E. & Sabanovic, A. (2014). Uzaktan Lazer Cerrahi İçin Kısıtlı Sistem Tabanlı Efendi Köle Denetleyicisi. I TOK 2014 (s. 675-680) http://research.sabanciuniv.edu/24776/1/2014_RA417_TOK2014_Eray_205.pdf

Zullo, H., Cline, K., Parker, M., Buckmire, R., George, J., Gurski, K., Larsen, J. J., Mellor, B. & Oberweiser, J. (2011). Student Surveys: What Do They Think? I K. Cline & H. Zullo (red.), Teaching Mathematics with Classroom Voting, With and Without Clicker (s. 29-34). Mathematical Association of America. http://www.maa.org/publications/ebooks/teaching-mathematics-with-classroom-voting-with-and-without-clickers

Zujevs, A., Osadcuks, V. & Ahrendt, P. (2015). Trends in Robotic Sensor Technologies for Fruit Harvesting: 2010-2015. Procedia Computer Science, 77, 227-233. https://doi.org/10.1016/j.procs.2015.12.378

Zhou, S., Helwa, M. K., Schoellig, A. P., Sarabakha, A. & Kayacan, E. (2019). Knowledge transfer between robots with similar dynamics for high-accuracy impromptu trajectory tracking. I 2019 18th European Control Conference, ECC 2019 [8796140] IEEE. 2019 18th European Control Conference, ECC 2019 https://doi.org/10.23919/ECC.2019.8796140

Zhang, C., Rossi, C. & Kayacan, E. (2017). Interval Type-2 Fuzzy-Neuro Control of Nonlinear Systems With Proved Overall System Stability. I Fuzzy Systems (FUZZ-IEEE), 2017 IEEE International Conference on (s. 1-6). IEEE. https://doi.org/10.1109/FUZZ-IEEE.2017.8015495

Yan, R-J., Wu, J., Yeung Lee, J., Manan Khan, A., Han, C-S., Kayacan, E. & Chen, I-M. (2016). A Novel Method for 3D Reconstruction: Division and Merging of Overlapping B-spline surfaces. Computer-Aided Design, 81, 14-23. https://doi.org/10.1016/j.cad.2016.08.007

Yan, R-J., Kayacan, E., Chen, I-M. & Kong Tiong, L. (2017). A novel building post-construction quality assessment robot: Design and prototyping. I Intelligent Robots and Systems (IROS), 2017 IEEE/RSJ International Conference on (s. 6020-6026). IEEE. https://doi.org/10.1109/IROS.2017.8206499

Yan, R-J., Leong Low, C., Duan, J., Liu, L., Kayacan, E., Chen, I-M. & Tiong, R. (2016). Development of a Novel Post-Construction Quality Assessment Robot System. I Control, Automation, Robotics and Vision (ICARCV), 2016 14th International Conference on (s. 1-6). IEEE . https://doi.org/10.1109/ICARCV.2016.7838741

Yan, R. J., Kayacan, E., Chen, I. M., Tiong, L. K. & Wu, J. (2019). QuicaBot: Quality Inspection and Assessment Robot. IEEE Transactions on Automation Science and Engineering, 16(2), 506-517. https://doi.org/10.1109/TASE.2018.2829927

Xu, L., Iosifidis, A. & Gabbouj, M. (2018). Weighted Linear Discriminant Analysis Based on Class Saliency Information. I 2018 25th IEEE International Conference on Image Processing (ICIP): Proceedings (s. 2306-2310). IEEE. https://doi.org/10.1109/ICIP.2018.8451614

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

Wilson Lee, Y. J., Mehndiratta, M. & Kayacan, E. (2018). Fly without borders with Additive Manufacturing: A microscale tilt-rotor Tricopter Design. I Proceedings of the 3rd International Conference on Progress in Additive Manufacturing (Pro-AM 2018) (s. 256-261) https://doi.org/10.25341/D43K5G

Westh Nicolajsen, H., Ahola, T., Fleury, A. M., Milkova Ilieva, T., Eg Larsen, J., Larsen, L. B., G. Nikolakopoulos, I., Z. Patrikakis, C., Pedersen, C. F., Roswall, R., Schultz, N. & Tolstrup Sørensen, L. (2007). Defining Usability of PN Services. Information Society Technologies, IST-FP6-IP-027396, My Personal Adaptive Global NET (MAGNET) Beyond, EU.

Waris, M. A., Iosifidis, A. & Gabbouj, M. (2017). CNN-based Edge Filtering for Object Proposals. Neurocomputing, 266, 631-640. https://doi.org/10.1016/j.neucom.2017.05.071

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

Wang, H., Mortensen, A. K., Mao, P., Boelt, B. & Gislum, R. (2019). Estimating the nitrogen nutrition index in grass seed crops using a UAV-mounted multispectralcamera. International Journal of Remote Sensing, 40(7), 2467-2482. https://doi.org/10.1080/01431161.2019.1569783

Wan, S., Chen, C. & Iosifidis, A. (2022). Editorial to special issue on cross-media learning for visual question answering. Image and Vision Computing, 118, [104355]. https://doi.org/10.1016/j.imavis.2021.104355

Wagner, S. R., Hansen, F. O., Pedersen, C. F., Memon, M., Beevi, F. H. A., Mathissen, M., Nielsen, C. & Wesby, O. L. (2013). CareStore Platform for Seamless Deployment of Ambient Assisted Living Applications and Devices. I Pervasive Computing Technologies for Healthcare (PervasiveHealth) 2013: 7th International Conference on (s. 240-243). IEEE. https://doi.org/10.4108/icst.pervasivehealth.2013.252110

Wagner, S. R., Stenner, R., Memon, M., Beevi, F. H. A. & Pedersen, C. F. (2014). Common Ambient Assisted Living Home Platform for Seamless Care. Abstract fra 8th International Conference on Pervasive Computing Technologies for Healthcare, Oldenburg, Tyskland.

Wagner, S., Kamper, C. H., Rasmussen, N. H., Ahrendt, P., Toftegaard, T. S. & Bertelsen, O. W. (2014). Reliable blood pressure self-measurement in the obstetric waiting room. Methods of Information in Medicine, 53(3), 225-234. https://doi.org/10.3414/ME13-01-0032

Wagner, S., Buus, N. H., Jespersen, B., Ahrendt, P., Bertelsen, O. W. & Toftegaard, T. S. (2013). Measurement adherence in the blood pressure self-measurement room. Telemedicine and e-Health, 19(11), 826-33. https://doi.org/10.1089/tmj.2013.0032

Wagner, S. R., Beevi, F. H. A., Pedersen, C. F., Miranda, J., Cabral, J. & Ravelo, B. (2016). Evaluation of Caregivers' First Time Use of a Seamless Deployment Platform. I Proceedings of the International Conference e-Health 2016 (s. 59-66). IADIS.

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

V. Topalev, A., Oniz, Y., Kayacan, E. & Kaynak, O. (2011). Neuro-Fuzzy Control of Antilock Braking System Using Sliding Mode Incremental Learning Algorithm. Neurocomputing, 74(11), 1883-1893. https://doi.org/10.1016/j.neucom.2010.07.035

V. Topalev, A., G. Shakev, N., Kaynak, O. & Kayacan, E. (2010). Neuro-adaptive Approach for Controlling a Quad-rotor Helicopter Using Sliding Mode Learning Algorithm. I IFAC Proceedings Volumes (10 udg., Bind 43, s. 94-99). Elsevier. https://doi.org/10.3182/20100826-3-TR-4015.00020

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

V. Topalev, A., Kayacan, E., Oniz, Y. & Kaynak, O. (2009). Adaptive Neuro-Fuzzy Control with Sliding Mode Learning Algorithm: Application to Antilock Braking System. I Asian Control Conference, 2009. ASCC 2009. 7th (s. 784-789). IEEE . https://ieeexplore.ieee.org/document/5276234/

Ugurlu, H. I., Kalkan, S. & Saranli, A. (2021). Reinforcement Learning versus Conventional Control for Controlling a Planar Bi-rotor Platform with Tail Appendage. Journal of Intelligent and Robotic Systems: Theory and Applications, 102(4), [77]. https://doi.org/10.1007/s10846-021-01412-3

Tøttrup, D., Skovgaard, S. L., Sejersen, J. L. F. & de Figueiredo, R. P. (2021). A fast and accurate approach to multiple-vehicle localization and tracking from monocular aerial images. Journal of Imaging, 7(12), [270]. https://doi.org/10.3390/jimaging7120270

Tøttrup, D., Skovgaard, S. L., Sejersen, J. L. F. & de Figueiredo, R. P. (2022). A Real-Time Method for Time-to-Collision Estimation from Aerial Images. Journal of Imaging, 8(3), [62]. https://doi.org/10.3390/jimaging8030062

Tzogka, C., Passalis, N., Iosifidis, A., Gabbouj, M. & Tefas, A. (2019). Less is more: Deep Learning using subjective annotations for sentiment analysis from social media. I 2019 IEEE 29th International Workshop on Machine Learning for Signal Processing, MLSP 2019: Proceedings [8918792] IEEE. https://doi.org/10.1109/MLSP.2019.8918792

Tu, G. J., Karstoft, H., Pedersen, L. J. & Jørgensen, E. (2013). Foreground detection using loopy belief propagation. Biosystems Engineering, 116(1), 88-96. https://doi.org/10.1016/j.biosystemseng.2013.06.011

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

Tu, G. J. & Karstoft, H. (2015). Logarithmic dyadic wavelet transform with its applications in edge detection and reconstruction. Applied Soft Computing, 26, 193-201. https://doi.org/10.1016/j.asoc.2014.09.044

Tu, G. J., Karstoft, H., Pedersen, L. J. & Jørgensen, E. (2015). Illumination and Reflectance Estimation with its Application in Foreground Detection. Sensors, 15(9), 21407-21426. https://doi.org/10.3390/s150921407

Tsapanos, N., Iosifidis, A. & Pitas, I. (2015). Mathematical preliminaries: graphs and matrices. I I. Pitas (red.), Graph-Based Social Media Analysis CRC Press. Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

Tsapanos, N., Tefas, A., Nikolaidis, N., Iosifidis, A. & Pitas, I. (2015). Fast Kernel Matrix Computation for Big Data Clustering. I Procedia Computer Science (s. 2445-2452). ELSEVIER. https://doi.org/10.1016/j.procs.2015.05.352

Tsantekidis, A., Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2017). Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks. I Business Informatics (CBI), 2017 IEEE 19th Conference on (s. 7-12). IEEE. https://doi.org/10.1109/CBI.2017.23

Tsantekidis, A., Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2017). Using Deep Learning to Detect Price Change Indications in Financial Markets. Proceedings of the European Signal Processing Conference, 2017, 2580-2584. https://doi.org/10.23919/EUSIPCO.2017.8081663

Tsantekidis, A., Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Using Deep Learning for price prediction by exploiting stationary limit order book features. Applied Soft Computing Journal, 93, [106401]. https://doi.org/10.1016/j.asoc.2020.106401

Tran, D. T., Iosifidis, A. & Gabbouj, M. (2018). Improving efficiency in convolutional neural networks with multilinear filters. Neural Networks, 105, 328-339. https://doi.org/10.1016/j.neunet.2018.05.017

Tran, D. T., Iosifidis, A., Kanniainen, J. & Gabbouj, M. (2019). Temporal Attention-Augmented Bilinear Network for Financial Time-Series Data Analysis. IEEE Transactions on Neural Networks and Learning Systems, 30(5), 1407 - 1418 . https://doi.org/10.1109/TNNLS.2018.2869225

Tran, D. T. & Iosifidis, A. (2019). Learning to Rank: A Progressive Neural Network Learning Approach. I 2019 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019 - Proceedings (s. 8355-8359). [8683711] IEEE. I E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings Bind 2019 May https://doi.org/10.1109/ICASSP.2019.8683711

Tran, D. T., Kiranyaz, S., Gabbouj, M. & Iosifidis, A. (2019). PyGOP: A Python library for Generalized Operational Perceptron algorithms. Knowledge-Based Systems, 182, [104801]. https://doi.org/10.1016/j.knosys.2019.06.009

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). [9308418] IEEE. 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 https://doi.org/10.1109/SSCI47803.2020.9308418

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Revideret 03.10.2022

AU Engineering