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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

Iosifidis, A., Tefas, A. & Pitas, I. (2013). Learning sparse representations for view-independent human action recognition based on fuzzy distances. Neurocomputing, 121, 344-353. https://doi.org/10.1016/j.neucom.2013.05.021

Iosifidis, A., Tefas, A. & Pitas, I. (2012). Dynamic action recognition based on Dynemes and Extreme Learning Machine. Pattern Recognition Letters, 34(15), 1890-1898. https://doi.org/10.1016/j.patrec.2012.10.019

Iosifidis, A., Tefas, A. & Pitas, I. (2013). Minimum Class Variance Extreme Learning Machine for Human Action Recognition. IEEE Transactions on Circuits and Systems for Video Technology, 23(11), 1968-1979. https://doi.org/10.1109/TCSVT.2013.2269774

Iosifidis, A., Tefas, A. & Pitas, I. (2012). Multidimensional Sequence Classification based on Fuzzy Distances and Discriminant Analysis. IEEE Transactions on Knowledge and Data Engineering, 25(11), 2564-2575. https://doi.org/10.1109/TKDE.2012.223

Iosifidis, A., Tefas, A. & Pitas, I. (2014). Regularized Extreme Learning Machine for Multi-view Semi-supervised Action Recognition. Neurocomputing, 145, 250-262. https://doi.org/10.1016/j.neucom.2014.05.036

Iosifidis, A., Tefas, A. & Pitas, I. (2014). Discriminant Bag of Words based Representation for Human Action Recognition. Pattern Recognition Letters, 49, 185-192. https://doi.org/10.1016/j.patrec.2014.07.011

Iosifidis, A., Tefas, A. & Pitas, I. (2014). Kernel Reference Discriminant Analysis. Pattern Recognition Letters, 49, 85-91. https://doi.org/10.1016/j.patrec.2014.06.013

Iosifidis, A., Tefas, A. & Pitas, I. (2015). Human Action Recognition based on Multi-view Regularized Extreme Learning Machine. International Journal on Artificial Intelligence Tools, 24(5), Artikel 1540020. https://doi.org/10.1142/S0218213015400205

Iosifidis, A., Marami, E., Tefas, A., Pitas, I. & Lyroudia, K. (2015). The MOBISERV-AIIA Eating and Drinking multi-view database for vision-based assisted living. Journal of Information Hiding and Multimedia Signal Processing, 6(2), 254-273. http://bit.kuas.edu.tw/~jihmsp/2015/vol6/JIH-MSP-2015-02-008.pdf

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

Iosifidis, A., Tefas, A. & Pitas, I. (2015). Distance-based Human Action Recognition using optimized class representations. Neurocomputing, 161, 47-55. https://doi.org/10.1016/j.neucom.2014.10.088

Iosifidis, A., Tefas, A. & Pitas, I. (2015). DropELM: Fast Neural Network Regularization with Dropout and DropConnect. Neurocomputing, 162, 57-66. https://doi.org/10.1016/j.neucom.2015.04.006

Mademlis, I., Iosifidis, A., Tefas, A., Nikolaidis, N. & Pitas, I. (2015). Exploiting Stereoscopic Disparity for Augmenting Human Activity Recognition Performance. Multimedia Tools and Applications, 75(19), 11641-11660. https://doi.org/10.1007/s11042-015-2719-x

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

Iosifidis, A. (2015). Extreme Learning Machine based Supervised Subspace Learning. Neurocomputing, 167, 158-164. https://doi.org/10.1016/j.neucom.2015.04.083

Iosifidis, A., Tefas, A. & Pitas, I. (2015). Class-specific Reference Discriminant Analysis with application in Human Behavior Analysis. IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS, 45(3), 315-326. https://doi.org/10.1109/THMS.2014.2379274

Malekian, R., Thakur, A., Nair, L. & Pedersen, C. F. (2018). A Sensor Based Peer to Peer Vehicle Data Sharing System, An Internet of Vehicles Approach. Journal of Internet Technology, 19(7), 2155-2162. http://jit.niu.edu.tw/article/view/1865

Miranda, J., Cabral, J., Banerjee, S., Grossmann, D., Pedersen, C. F. & Wagner, S. R. (2017). Analysis of OPC Unified Architecture for Healthcare Applications. I 2017 22nd IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2017: EFTA 2017 (s. 1-4). IEEE. https://doi.org/10.1109/ETFA.2017.8247771

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

Aytekin, C., Kiranyaz, S., Iosifidis, A. & Gabbouj, M. (2016). Recent advances in salient object detection -- Towards object recognition in big media data. Futura – Big Data, 35(2), 80-92. https://tutcris.tut.fi/portal/en/publications/recent-advances-in-salient-object-detection--towards-object-recognition-in-big-media-data(1e2959cf-8622-4243-b78b-6eb03f34a0ce).html

Iosifidis, A., Tefas, A. & Pitas, I. (2015). Graph Embedded Extreme Learning Machine. IEEE Transactions on Cybernetics, 46(1), 311-324. https://doi.org/10.1109/TCYB.2015.2401973

Iosifidis, A. & Gabbouj, M. (2016). Multi-class Support Vector Machine Classifiers using Intrinsic and Penalty Graphs. Pattern Recognition, 55, 231-246. https://doi.org/10.1016/j.patcog.2016.02.002

Patrona, F., Iosifidis, A., Tefas, A., Nikolaidis, N. & Pitas, I. (2016). Visual Voice Activity Detection in the Wild. IEEE Transactions on Multimedia, 18(6), 967-977. Artikel 7420734. http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7420734

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

Mygdalis, V., Iosifidis, A., Tefas, A. & Pitas, I. (2016). Graph Embedded One-Class Classifiers for media data classification. Pattern Recognition, 60, 585-595. https://doi.org/10.1016/j.patcog.2016.05.033

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. Artikel 7494969. https://doi.org/10.1109/TIFS.2016.2582562

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

Iosifidis, A., Tefas, A. & Pitas, I. (2016). Approximate Kernel Extreme Learning Machine for Large-Scale Data Classification. Neurocomputing, 219, 210-220. https://doi.org/10.1016/j.neucom.2016.09.023

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

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

Kiranyaz, S., Ince, T., Iosifidis, A. & Gabbouj, M. (2016). Progressive Operational Perceptrons. Neurocomputing, 224, 142-154. https://doi.org/10.1016/j.neucom.2016.10.044

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

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

Iosifidis, A. & Gabbouj, M. (2017). Class-Specific Kernel Discriminant Analysis revisited: further analysis and extensions. IEEE Transactions on Cybernetics, 47(12), 4485-4496. Artikel 7590015. https://doi.org/10.1109/TCYB.2016.2612479

Aytekin, C., Iosifidis, A., Kiranyaz, S. & Gabbouj, M. (2016). Learning Graph Affinities for Spectral Graph-based Salient Object Detection. Pattern Recognition, 64, 159-167. https://doi.org/10.1016/j.patcog.2016.11.005

Cao, G., Iosifidis, A. & Gabbouj, M. (2017). Multi-view Nonparametric Discriminant Analysis for Image Retrieval and Recognition. IEEE Signal Processing Letters, 24(10), 1537-1541. Artikel 8023967. https://doi.org/10.1109/LSP.2017.2748392

Cao, G., Iosifidis, A., Chen, K. & Gabbouj, M. (2018). Generalized Multi-View Embedding for Visual Recognition and Cross-Modal Retrieval. IEEE Transactions on Cybernetics, 48(9), 2542-2555. Artikel 8026149. https://doi.org/10.1109/TCYB.2017.2742705

Christiansen, M. P., Nyholm Jørgensen, R., Laursen, M. S. & Gislum, R. (2017). UAV LIDAR biomass estimation/Using Sentinel-1 to estimate yield potential. Poster session præsenteret på DIGIT, Aarhus, Danmark.

Kragh, M. F., Christiansen, P., Laursen, M. S., Larsen, M., Steen, K. A., Green, O., Karstoft, H. & Jørgensen, R. N. (2017). FieldSAFE: Dataset for Obstacle Detection in Agriculture. Sensors, 17(11), Artikel 2579. https://doi.org/10.3390/s17112579

Madsen, S. L., Karstoft, H., Nyholm Jørgensen, R., Nørremark, M., Khokhar, Y., Gomez, J. S., pier van Gosliga, S. & Jaakkola, K. (2017). Quantifying behaviour of dairy cows via multi-stage Support Vector Machines. I D. Berckmans & A. Keita (red.), Book of proceedings: 8th European Conference on Precision Livestock Farming: ECPLF 2017 (s. 90-100)

Rasmussen, S., Nyboe, S. N., Mai, S. S. & Larsen, J. J. (2017). A Robust Framework for Cancellation of MSK Interference in TEM Data. I 2nd European Airborne Electromagnetics Conference 2017, Held at Near Surface Geoscience Conference and Exhibition 2017 (s. 121-125). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.201702172

Rasmussen, S., Skovgaard Nyboe, N., Mai, S. & Larsen, J. J. (2017). Noise properties of Fourier deconvolution for time-domain electromagnetic soundings. Geophysics, 82(5), 257-266. https://doi.org/10.1190/geo2016-0588.1

Dyrmann, M., Nyholm Jørgensen, R. & Midtiby, H. S. (2017). Detection of weed locations in leaf occluded cereal crops using a fully convolutional neural network. Advances in Animal Biosciences, 8(2), 842-847. https://doi.org/10.1017/S2040470017000206

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., Sørensen, R. A., Laursen, M. S., Rasmussen, J. & Nielsen, J. (2017). FutureCropping Generering af tidselkort med Pix4D, DeepLearning og QGIS 18AUG2017. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=3X8h4U4o2-o

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

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

Sridharan, K. S., Højlund, A., Johnsen, E. L., Sunde, N., Johansen, L. G., Beniczky, S. & Østergaard, K. (2017). Differentiated effects of deep brain stimulation and medication on somatosensory processing in Parkinson's disease. Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 128(7), 1327-1336. https://doi.org/10.1016/j.clinph.2017.04.014

Laursen, M. S., Nyholm Jørgensen, R., Gislum, R. & Christiansen, M. P. (2017). First attempt at crop mapping with Velodyne VLP16 and Matrice 100. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=rzTScFbkdG0

Jeppesen, J. H., Jacobsen, R. H., Nyholm Jørgensen, R., Halberg, A. & Toftegaard, T. S. (2017). Identification of High-Variation Fields based on Open Satellite Imagery. Advances in Animal Biosciences, 8(2), 388-393. https://doi.org/10.1017/S2040470017000693

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Revideret 10.08.2023

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AU Engineering