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Institut for Elektro- og Computerteknologi

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

Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2020). Efficient Bloch-equation solvers for surface nuclear magnetic Resonance. Abstract fra AGU Fall Meeting 2020.

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

Grombacher, D., Liu, L., Osterman, G. K. & Larsen, J. J. (2021). Mitigating Narrowband Noise Sources Close to the Larmor Frequency in Surface NMR. IEEE Geoscience and Remote Sensing Letters, 18(8), 1376-1380. https://doi.org/10.1109/LGRS.2020.3000639

Larsen, J. J., Liu, L., Grombacher, D., Osterman, G. K. & Auken, E. (2020). Apsu — A new compact surface nuclear magnetic resonance system for groundwater investigation. Geophysics, 85(2), JM1-JM11. https://doi.org/10.1190/geo2018-0779.1

Jeppesen, J. H., Jacobsen, R. H. & Jorgensen, R. N. (2020). Crop Type Classification based on Machine Learning with Multitemporal Sentinel-1 Data. I A. Trost, A. Zemva & A. Skavhaug (red.), 2020 23rd Euromicro Conference on Digital System Design (DSD) (s. 557-564). IEEE. https://doi.org/10.1109/DSD51259.2020.00092

Barfod, A. A. S., Lévy, L. & Larsen, J. J. (2021). Automatic processing of time domain induced polarization data using supervised artificial neural networks. Geophysical Journal International, 224(1), 312-325. https://doi.org/10.1093/gji/ggaa460

Nielsen, A. H., Wagner, A., Iosifidis, A. & Karstoft, H. (2020). Cloud Nowcasting on Satellite Images: A Novel Dataset and Experimental Comparisons. https://ams.confex.com/ams/2020Annual/meetingapp.cgi/Paper/365696

Nielsen, A. H., Iosifidis, A. & Karstoft, H. (2020). CloudCast: A Satellite-Based Dataset and Baseline for Forecasting Clouds. Abstract fra European Conference on Computer Vision Workshop . https://drive.google.com/file/d/1_TV20JCIyBaetN6Y1mt7K5FeMx431Rr3/view

Asif, M. R., Bording, T. S., Barfod, A. A. S., Zhang, B., Larsen, J. J. & Auken, E. (2020). Improving computational efficiency of forward modelling for ground-based time-domain electromagnetic data using neural networks. Abstract fra EGU:General assembly 2020 , Vienna , Østrig. https://doi.org/10.5194/egusphere-egu2020-7067

Lang, X., Rehman, N. U., Zhang, Y., Xie, L. & Su, H. (2020). Median ensemble empirical mode decomposition. Signal Processing, 176, Artikel 107686. https://doi.org/10.1016/j.sigpro.2020.107686

Rehman, N. U., Naveed, K. & Khan, B. (2019). Data-Driven Multivariate Signal Denoising Using Mahalanobis Distance. IEEE Signal Processing Letters, 26(9), 1408-1412. https://doi.org/10.1109/LSP.2019.2932715

Rehman, N. U. & Aftab, H. (2019). Multivariate Variational Mode Decomposition. IEEE Transactions on Signal Processing, 67(23), 6039. Artikel 8890883. https://doi.org/10.1109/TSP.2019.2951223

Gul, S., Siddiqui, M. F. & Rehman, N. U. (2020). FPGA-Based Design for Online Computation of Multivariate Empirical Mode Decomposition. IEEE Transactions on Circuits and Systems Part 1: Regular Papers, 67(12), 5040-5050. Artikel 9159690. https://doi.org/10.1109/TCSI.2020.3012351

Naveed, K. & Rehman, N. U. (2020). Wavelet based multivariate signal denoising using Mahalanobis distance and EDF statistics. IEEE Transactions on Signal Processing, 68, 5997-6010. Artikel 9234624. https://doi.org/10.1109/TSP.2020.3029659

Naveed, K., Akhtar, M. T., Siddiqui, M. F. & Rehman, N. U. (2021). A statistical approach to signal denoising based on data-driven multiscale representation. Digital Signal Processing, 108, Artikel 102896. https://doi.org/10.1016/j.dsp.2020.102896

Morales, T., Sarabakha, A. & Kayacan, E. (2020). Image Generation for Efficient Neural Network Training in Autonomous Drone Racing. I 2020 International Joint Conference on Neural Networks (IJCNN) Artikel 9206943 IEEE. https://doi.org/10.1109/IJCNN48605.2020.9206943

Kass, M. A., Christiansen, A. V., Auken, E. & Larsen, J. J. (2021). Efficient reduction of powerline signals in magnetic data acquired from a moving platform. IEEE Transactions on Geoscience and Remote Sensing, 59(8), 7137-7146. Artikel 9246269. https://doi.org/10.1109/TGRS.2020.3029658

Iosifidis, A. (2020). Class mean vector component and discriminant analysis. Pattern Recognition Letters, 140, 207-213. https://doi.org/10.1016/j.patrec.2020.10.014

Bozcan, I. & Kayacan, E. (2020). AU-AIR: A Multi-modal Unmanned Aerial Vehicle Dataset for Low Altitude Traffic Surveillance. I 2020 IEEE International Conference on Robotics and Automation (ICRA) (s. 8504-8510). IEEE. https://doi.org/10.1109/ICRA40945.2020.9196845

Afshari-Igder, M., Rafiei Foroushani, M., Boudjadar, J. & Khooban, M. H. (2021). Reliability and Safety Improvement of Emission-Free Ships: Systemic Reliability Centered Maintenance. IEEE Transactions on Transportation Electrification, 7(1), 256-266. Artikel 9220168. https://doi.org/10.1109/TTE.2020.3030082

Skovsen, S. K., Haraldsson, H., Davis, A., Karstoft, H. & Belongie, S. (2020). Decoupled Localization and Sensing with HMD-based AR for Interactive Scene Acquisition. I 2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct) (s. 167-171). Artikel 9288396 IEEE. https://doi.org/10.1109/ISMAR-Adjunct51615.2020.00053

Skovsen, S. K. (2021). Mixed Crop Mapping by Species Discrimination using Data Driven Computer Vision and Simulated Data. Århus Universitet.

Farkhani, S., Skovsen, S. K., Mortensen, A. K., Laursen, M. S., Nyholm Jørgensen, R. & Karstoft, H. (2020). Initial evaluation of enriching satellite imagery using sparse proximal sensing in precision farming. I C. M. U. Neale & A. Maltese (red.), Remote Sensing for Agriculture, Ecosystems, and Hydrology XXII (Bind 11528). Artikel 115280A SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2573626

Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Deep Adaptive Input Normalization for Time Series Forecasting. IEEE Transactions on Neural Networks and Learning Systems, 31(9), 3760-3765. https://doi.org/10.1109/TNNLS.2019.2944933

Chumachenko, K., Mannisto, A., Iosifidis, A. & Raitoharju, J. (2020). Machine Learning Based Analysis of Finnish World War II Photographers. IEEE Access, 8, 144184-144196. Artikel 9159591. https://doi.org/10.1109/ACCESS.2020.3014458

Mehndiratta, M. & Kayacan, E. (2020). Gaussian Process-based Learning Control of Aerial Robots for Precise Visualization of Geological Outcrops. I 2020 European Control Conference (ECC) (s. 10-16). Artikel 9143655 IEEE.

Laakom, F., Passalis, N., Raitoharju, J., Nikkanen, J., Tefas, A., Iosifidis, A. & Gabbouj, M. (2020). Bag of Color Features for Color Constancy. IEEE Transactions on Image Processing, 29, 7722-7734. Artikel 9130881. https://doi.org/10.1109/TIP.2020.3004921

Sohrab, F., Raitoharju, J., Iosifidis, A. & Gabbouj, M. (2020). Ellipsoidal Subspace Support Vector Data Description. IEEE Access, 8, 122013-122025. Artikel 9133428. https://doi.org/10.1109/ACCESS.2020.3007123

Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Adaptive Normalization for Forecasting Limit Order Book Data Using Convolutional Neural Networks. I 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings (s. 1713-1717). Artikel 9054321 IEEE. https://doi.org/10.1109/ICASSP40776.2020.9054321

Sommer, W. L. & Iosifidis, A. (2020). Text-To-Image Synthesis Method Evaluation Based on Visual Patterns. I 2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings (s. 4097-4101). Artikel 9053034 IEEE. https://doi.org/10.1109/ICASSP40776.2020.9053034

Banaei, M., Ghanami, F., Rafiei Foroushani, M., Boudjadar, J. & Khooban, M. H. (2020). Energy Management of Hybrid Diesel/Battery Ships in Multidisciplinary Emission Policy Areas. Energies, 13(16), Artikel 4179. https://doi.org/10.3390/en13164179

Hansen, B., Christiansen, A. V., Dalgaard, T., Jørgensen, F., Iversen, B. V., Larsen, J. J., Kjærgaard, C., Jacobsen, B. H., Auken, E., Hojberg, A. L. & Schaper, S. (2020). Danish review on advances in assessing: N retention in the subsurface in relation to future targeted N-regulation of agriculture. GEUS, Geological Survey of Denmark and Greenland. GEUS Rapport Bind 2020 Nr. 11 https://mapfield.dk/media/21858/d26_synthesis_report_mapfield.pdf

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

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

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, Artikel 115917. https://doi.org/10.1016/j.image.2020.115917

Ntakaris, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Mid-price prediction based on machine learning methods with technical and quantitative indicators. PLOS ONE, 15(6 June), Artikel e0234107. https://doi.org/10.1371/journal.pone.0234107

Passalis, N., Tefas, A., Kanniainen, J., Gabbouj, M. & Iosifidis, A. (2020). Temporal logistic neural Bag-of-Features for financial time series forecasting leveraging limit order book data. Pattern Recognition Letters, 136, 183-189. https://doi.org/10.1016/j.patrec.2020.06.006

Rafiei Foroushani, M., Niknam, T., Aghaei, J., Shafie-khah, M. & P.S.Catalão, J. (2018). Probabilistic Load Forecasting Using an Improved Wavelet Neural Network Trained by Generalized Extreme Learning Machine. IEEE Transactions on Smart Grid, 9(6), 6961 - 6971. Artikel 8298533. https://doi.org/10.1109/TSG.2018.2807845

Farsizadeh, H., Gheisarnejad, M., Mosayebi, M., Rafiei Foroushani, M. & Khooban, M. H. (2020). An Intelligent and Fast Controller for DC/DC Converter Feeding CPL in a DC Microgrid. IEEE Transactions on Circuits and Systems II: Express Briefs, 67(6), 1104-1108. Artikel 8764402. https://doi.org/10.1109/TCSII.2019.2928814

Hasanvand , S., Rafiei Foroushani, M., Gheisarnejad, M. & Khooban, M. H. (2020). Reliable Power Scheduling of an Emission-Free Ship: Multi-Objective Deep Reinforcement Learning. IEEE Transactions on Transportation Electrification, 6(2), 832-843. Artikel 9046850. https://doi.org/10.1109/TTE.2020.2983247

Bonatti, R., Wang, W., Ho, C., Ahuja, A., Gschwindt, M., Camci, E., Kayacan, E., Choudhury, S. & Scherer, S. (2020). Autonomous aerial cinematography in unstructured environments with learned artistic decision-making. Journal of Field Robotics, 37(4), 606-641. https://doi.org/10.1002/rob.21931

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, Artikel 106401. https://doi.org/10.1016/j.asoc.2020.106401

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

Krestenitis, M., Passalis, N., Iosifidis, A., Gabbouj, M. & Tefas, A. (2020). Recurrent bag-of-features for visual information analysis. Pattern Recognition, 106, Artikel 107380. https://doi.org/10.1016/j.patcog.2020.107380

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

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

Letafat, A., Rafiei, M., Ardeshiri, M., Sheikh, M., Banaei, M., Boudjadar, J. & Khooban, M. H. (2020). An Efficient and Cost-Effective Power Scheduling in Zero-Emission Ferry Ships. Complexity, 2020, Artikel 6487873. https://doi.org/10.1155/2020/6487873

Rafiei Foroushani, M., Boudjadar, J. & Khooban, M. H. (2021). Energy Management of a Zero-Emission Ferry Boat with a Fuel Cell-Based Hybrid Energy System: Feasibility Assessment. IEEE Transactions on Industrial Electronics, 68(2), 1739-1748. https://doi.org/10.1109/TIE.2020.2992005

Madsen, S. L., Mathiassen, S. K., Dyrmann, M., Laursen, M. S., Paz, L.-C. & Nyholm Jørgensen, R. (2020). Open Plant Phenotype Database of Common Weeds in Denmark. Remote Sensing, 12(8), Artikel 1246. https://doi.org/10.3390/rs12081246

Raza, M. A., Qi, C., Asif, M. R. & Khan, M. A. (2020). An adaptive approach for multi-national vehicle license plate recognition using multi-level deep features and foreground polarity detection model. Applied Sciences, 10(6), Artikel 2165. https://doi.org/10.3390/app10062165

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AU Engineering