Institut for Elektro- og Computerteknologi

Aarhus Universitets segl

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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Iosifidis, A., Tefas, A., Pitas, I. & Gabbouj, M. (2017). Big Media Data Analysis. Signal Processing: Image Communication, 59, 105-108. https://doi.org/10.1016/j.image.2017.10.004
Giselsson, T. M., Nyholm Jørgensen, R., Jensen, P. K., Dyrmann, M. & Midtiby, H. S. (2017). A Public Image Database for Benchmark of Plant Seedling Classification Algorithms. arxiv.org. https://arxiv.org/pdf/1711.05458
Thanh Tran, D., Gabbouj, M. & Iosifidis, A. (2017). Multilinear Class-Specific Discriminant Analysis. Pattern Recognition Letters, 100, 131-136. https://doi.org/10.1016/j.patrec.2017.10.027
Nyholm Jørgensen, R. & Skovsen, S. (2017). Automatisk kløvergræsestimering. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=Kx_8ku90XO4&t=955s
Nyholm Jørgensen, R. & Dyrmann, M. (2017). Automatisk genkendelse af ukrudt. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=xw9p3S-GZG8&t=794s
Nyholm Jørgensen, R. (2017). Metatilgangen til Deep Learning. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=moLU3QvWIRM&t=355s
Cao, G., Iosifidis, A. & Gabbouj, M. (2018). Neural class-specific regression for face verification. IET Biometrics, 7(1), 63-70. https://doi.org/10.1049/iet-bmt.2017.0081
Aytekin, C., Iosifidis, A. & Gabbouj, M. (2018). Probabilistic Saliency Estimation. Pattern Recognition, 74, 359-372. https://doi.org/10.1016/j.patcog.2017.09.023
Sørensen, R. A., Rasmussen, J., Nielsen, J. & Nyholm Jørgensen, R. (2017). Thistle detection using convolutional neural networks: EFITA 2017 Presentation. Billeder, Video- og Lydoptagelser (digital), YouTube. https://www.youtube.com/watch?v=_G_xLchBOl4
Iosifidis, A., Mouroutsos, S. G. & Gasteratos, A. (2011). A hybrid static/active video surveillance system. International Journal of Optomechatronics, 5(1), 80-95. https://doi.org/10.1080/15599612.2011.553252
Iosifidis, A., Tefas, A. & Pitas, I. (2011). Activity based Person Identification using Fuzzy Representation and Discriminant Learning. IEEE Transactions on Information Forensics and Security, 7(2), 530-542. https://doi.org/10.1109/TIFS.2011.2175921
Iosifidis, A., Tefas, A., Nikolaidis, N. & Pitas, I. (2011). Multi-view Human Movement Recognition based on Fuzzy Distances and Linear Discriminant Analysis. Computer Vision and Image Understanding, 116(3), 347-360. https://doi.org/10.1016/j.cviu.2011.08.008
Iosifidis, A., Tefas, A. & Pitas, I. (2012). View-invariant action recognition based on Artificial Neural Networks. IEEE Transactions on Neural Networks and Learning Systems, 23(3), 412-424. https://doi.org/10.1109/TNNLS.2011.2181865
Lausdahl, K. G., Bjerge, K., Bokhove, T., Groen, F. & Larsen, P. G. (2017). Transitioning from Crescendo to INTO-CPS. I J. S. Fitzgerald, P. W. V. Tran-Jørgensen & T. Oda (red.), The 15th Overture Workshop: New Capabilities and Applications for Model-based Systems Engineering: Proceedings (s. 16-30). Newcastle University.
Iosifidis, A., Tefas, A. & Pitas, I. (2012). Multi-view Action Recognition Based on Action Volumes, Fuzzy Distances and Cluster Discriminant Analysis. Signal Processing, 93(6), 1445-1457. https://doi.org/10.1016/j.sigpro.2012.08.015
Iosifidis, A., Tefas, A. & Pitas, I. (2013). On the optimal class representation in Linear Discriminant Analysis. IEEE Transactions on Neural Networks and Learning Systems, 24(9), 1491-1497. https://doi.org/10.1109/TNNLS.2013.2258937
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. https://doi.org/10.3966/160792642018121907018
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. https://doi.org/10.1109/TMM.2016.2535357
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. (2017). 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. (2017). 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

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