This page was last updated in 2022. A more complete list can be found in Google Scholar and DBLP.

Preprints under review in journals

• N. Zehtabiyan-Rezaie, A. Iosifidis and M. Abkar, "Physics-guided machine learning for wind-farm power prediction: Toward interpretability and generalizability", arXiv:2212.04188

• M. Magris and A. Iosifidis, "Bayesian Learning for Neural Networks: an algorithmic survey", arXiv:2211.11865

• M. Refiei, J. Raitoharju and A. Iosifidis, "Computer Vision on X-ray Data in Industrial Production and Security Applications: A survey", arXiv:2211.05565

• A. Bakhtiarnia, Q. Zhang and A. Iosifidis, "Efficient High-Resolution Deep Learning: A Survey", arXiv:2207.1350

• M. Shabani, M. Magris, G. Tzagkarakis, J. Kanniainen and A. Iosifidis, "Predicting the State of Synchronization of Financial Series using Cross Recurrence Plots", arXiv:2210.14605

• M. Refiei, D. T. Tran and A. Iosifidis, "Recognition of Defective Minear Wool using Pruned ResNet Models", arXiv:2211.00466

• M. Shabani, D. T. Tran, J. Kanniainen and A. Iosifidis, "Augmented Bilinear Network for Incremental Multi-Stock Time-Series Classification", arXiv:2207.11577

• I. Oleksiienko, P. Nousi, N. Passalis, A. Tefas and A. Iosifidis, “VPIT: Real-time Embedded Single Object 3D Tracking Using Voxel Pseudo Images”, arXiv:2206.02619 

• A. Cavaga, N. Li, A. Iosifidis and Q. Zhang, "Semantic Communication Enabling Robust Edge Intelligence for Time-Critical IoT Applications", arXiv:2211.13787

• A. Mannisto, M. Seker, A. Iosifidis and J. Raitoharju, "Automatic Image Content Extraction: Operationalizing Machine Learning in Humanistic Photographic Studies of Large Visual Archives", arXiv:2204.02149

• L. Hedegaard, N. Heidari and A. Iosifidis, “Online Skeleton-based Action Recognition with Continual Spatio-Temporal Graph Convolutional Networks”, arXiv:2203.11009 

• D.T. Tran, J. Kanniainen and A. Iosifidis, “How informative is the order book beyond the best levels? Machine Learning perspective”, arXiv:2203.07922 

• F. Laakom, J. Raitoharju, N. Passalis, A. Iosifidis and M. Gabbouj, "Non-Linear Spectral Dimensionality Reduction Under Uncertainty", arXiv:2202.04678

• R. Jensen and A. Iosifidis, "Fighting Money Laundering with Statistics and Machine Learning: An Introduction and Review", arXiv:2201.04207

• D.T. Tran, M. Gabbouj and A. Iosifidis, “Multilinear Compressive Learning with Prior Knowledge”, arXiv:2002.07203

• J. Raitoharju and A. Iosifidis, “Null Space Analysis for Class-Specific Discriminant Learning”, arXiv:1908.04562

Editorials

1. S. Wan, C. Chen and A. Iosifidis, “Cross-Media Learning for Visual Question Answering”, Image and Vision Computing, 104355, 2022

2. A. Iosifidis and A. Tefas, “Deep Learning for Visual Content Analysis”, Signal Processing: Image Communication, vol 83, 115806, 2020

3. A. Iosifidis, A. Tefas, I. Pitas and M. Gabbouj, “Big Media Data Analysis”, Signal Processing: Image Communication, vol. 59, pp. 105-108, 2017

Journal papers

1. M. Seker, A. Mannisto, A. Iosifidis and J. Raitoharju, “Automatic Social Distance Estimation from Images: Performance Evaluation, Test Benchmark, and Algorithm”, Machine Learning with Applications, accepted October 2022

2. I. Oleksiienko, D. T. Tran and A. Iosifidis, “Variational Neural Networks implementation in Pytorch and JAX”, Software Impacts, accepted October 2022

3. R. I. T. Jensen and A. Iosifidis, “Qualifying and Raising Anti-Money Laundering Alarms with Deep Learning”, Expert Systems with Applications, accepted October 2022

4. C. M. Legaard, T. Schranz, G. Schweiger, J. Drgona, B. Falay, C. Gomes, A. Iosifidis, M. Abkar and P. G. Larsen, “Constructing Neural Network-Based Models for Simulating Dynamical Systems”, ACM Computing Surveys, accepted October 2022 

5. F. Sohrab, A. Iosifidis, M. Gabbouj and J. Raitoharju, "Graph-Embedded Subspace Support Vector Data Description", Pattern Recognition, accepted August 2022

6. N. Li, A. Iosifidis and Q. Zhang, “Collaborative Edge Computing for Distributed CNN Inference Acceleration using Receptive field-based Segmentation”, Computer Networks, accepted July 2022 

7. A. Bakhtiarnia, Q. Zhang and A. Iosifidis, “Single-Layer Vision Transformer for More Accurate Early Exits with Less Overhead”, Neural Networks, accepted June 2022 

8. M. R. Mann, A. Iosifidis, J. U. Jepsen, J. M. Welker, M. J. J. E. Loonen and T. T. Hoye, “Automatic flower detection and phenology monitoring using time-lapse cameras and deep learning”, Remote Sensing in Ecology and Conservation, accepted May 2022 

9. N. Zehtabiyan-Rezaie, A. Iosifidis and M. Abkar, “Data-driven fluid mechanics of wind farms: A review”, Journal of Renewable and Sustainable Energy, accepted April 2022 

10. D.T. Tran, N. Passalis, A. Tefas, M. Gabbouj and A. Iosifidis, "Attention-based Neural Bag-of-Features Learning for Sequence Data", IEEE Access, accepted April 2022

11. A.H. Nielsen, A. Iosifidis and H. Karstoft, “Forecasting large-scale circulation regimes using deformable convolutional neural networks and global spatiotemporal climate data”, Scientific Reports, vol. 12, article number 8395, 2022 

12. F. Laakom, J. Raitoharju, N. Passalis, A. Iosifidis and M. Gabbouj, "Graph Embedding with Data Uncertainty", IEEE Access, accepted Febr. 2022

13. K. Chumachenko, A. Iosifidis and M. Gabbouj, “Feedforward Neural Networks Initialization based on Discriminant Learning”, Neural Networks, vol. 146, pp. 220-229, 2022

14. L.H. Morsing, O.A. Sheikh-Omar and A. Iosifidis, “Supervised Domain Adaptation: A Graph Embedding Perspective and a new experimental protocol”, IEEE Transactions on Image Processing, vol. 30, pp. 8619-8631, 2021

15. D.T. Tran, M. Gabbouj and A. Iosifidis, “Remote Multilinear Compressive Learning with Adaptive Compression”, IEEE Internet of Things journal, accepted September 2021

16. A.H. Nielsen, A. Iosifidis and H. Karstoft, “IrradianceNet: Spatiotemporal Deep Learning Model for Satellite-Derived Solar Irradiance Nowcasting”, Solar Energy, vol. 228, pp. 659-669, 2021

17. B. Leporowski and A. Iosifidis, "Visualising Deep Network's Time-Series Representations", Neural Computing and Applications, vol. 33, pp. 1689-1698, 2021

18. N. Heidari and A. Iosifidis, "Progressive Graph Convolutional Networks for Semi-Supervised Node Classification", IEEE Access, vol. 9, pp. 81957-81968, 2021

19. L. Xu, J. Raitoharju, A. Iosifidis and M. Gabbouj, "Saliency-based Weighted Multi-label Linear Discriminant Analysis", IEEE Transactions on Cybernetics, accepted March 2021

20. S. Kiranyaz, J. Malik, H.B. Abdallah, T. Ince, A. Iosifidis and M. Gabbouj, "Self-Organized Operational Neural Networks with Generative Neurons", Neural Networks, vol. 140, pp. 294-308, 2021

21. A.H. Nielsen, A. Iosifidis and H. Karstoft, "CloudCast: A Satelite-based Dataset and Baseline for Forecasting Clouds", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 14, pp. 3485-3494, 2021

22. R. Kharghanian, A. Peiravi, F. Moradi and A. Iosifidis, "Pain Detection using Batch Normalized Discriminant Restricted Botzmann Machine Layers", Journal of Visual Communication and Image Representation, vol. 76:103062, 2021

23. F. Laakom, J. Raitoharju, A. Iosifidis, J. Nikkanen and M. Gabbouj, “INTEL-TAU: A Color Constancy Dataset”, IEEE Access, vol. 9, pp. 39560-39567, 2021

24. N. Passalis, J. Kanniainen, M. Gabbouj, A. Iosifidis and A. Tefas, "Forecasting Financial Time Series using Robust Deep Adaptive Input Normalization", Journal of Signal Processing Systems, DOI: 10.1007/s11265-020-01624-0, 2021

25. S. Kiranyaz, J. Malik, H.B. Abdallah, T. Ince, A. Iosifidis and M. Gabbouj, “Exploiting Heterogeneity in Operational Neural Networks by Synaptic Plasticity”, Neural Computing and Applications, DOI: 10.1007/s00521-020-05543-w, 2021 

26. T.T. Høye, J. Ärje, K. Bjerge, O.L.P. Hansen, A. Iosifidis, F. Leese, H.M.R. Mann, K. Meissner, C. Melvad and J. Raitoharju, “Deep learning and computer vision will transform entomology”, Proceedings of the National Academy of Sciences of the United States of America, vol. 118, no. 2, ID: 2020-02545RRR, 2021 

27. J. Malik, S. Kiranyaz, R.I. Al-Raoush, O. Monga, P. Garnier, S. Foufou, A. Bouras, A. Iosifidis, M. Gabbouj, and P.C. Baveye, “3D Quantum Cuts for Automatic Segmentation of Porous Media in Tomography Images”, Computers and Geosciences, accepted November 2021

28. A. Iosifidis, "Class Mean Vector Component and Discriminant Analysis", Pattern Recognition Letters, vol. 140, no. 2, pp. 207-213, 2020

29. A. Iosifidis, "Probabilistic Class-Specific Discriminant Analysis", IEEE Access, vol. 8, pp. 183847-183855, 2020 

30. K. Chumachenko, J. Raitoharju, A. Iosifidis and M. Gabbouj, "Speed-up and multi-view extensions to Subclass Discriminant Analysis", Pattern Recognition, vol. 111, 107660, 2021

31. C. Gautam, A. Riwari, P.K. Mishra, S. Suresh, A. Iosifidis and M. Tanveer, “Graph-Embedded Multi-layer Kernel Ridge Regression for One-class Classification”, Cognitive Computation, vol. 13, pp. 552-569, 2021 

32. F. Sohrab, J. Raitoharju, A. Iosifidis and M. Gabbouj, "Multimodal Subspace Support Vector Data Description", Pattern Recognition, vol. 110, 107648, 2021

33. N. Passalis, A. Iosifidis, M. Gabbouj and A. Tefas, “Hypersphere-based Weight Imprinting for Few-shot Learning on Embedded Devices”, IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 2, pp. 925-930, 2021

34. D.T. Tran, M. Yamac, A. Degerli, M. Gabbouj and A. Iosifidis, “Multilinear Compressive Learning”, IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 4, pp. 1512-1524, 2021

35. G. Cao, A. Iosifidis, M. Gabbouj, V. Raghavan and R. Gottumukkala, "Deep Multi-view Learning to Rank", IEEE Transactions on Knowledge and Data Engineering, vol. 33, no. 4, pp. 1426-1438, 2021

36. K. Chumachenko, A. Mannisto, A. Iosifidis and J. Raitoharju, "Machine Learning based Analysis of Finnish World War II Photographers", IEEE Access, vol. 8, pp. 144184 – 144196, 2020

37. F. Sohrab, J. Raitoharju, A. Iosifidis and M. Gabbouj, “Ellipsoidal Subspace Support Vector Data Description”, IEEE Access, vol. 8, pp. 122013-122025, 2020

38. F. Laakom, N. Passalis, J. Raitoharju, J. Nikkanen, A. Tefas, A. Iosifidis and M. Gabbouj, “Bag of Color Features for Color Constancy”, IEEE Transactions on Image Processing, vol. 29, pp. 7722 – 7734, 2020 

39. J. Arje, J. Raitoharju, A. Iosifidis, V. Tirronen, K. Meissner, M. Gabbouj, S. Kiranyaz and S. Karkkainen, “Human experts vs. machines in taxa recognition”, Signal Processing: Image Communication, vol. 87:115917, pp. 1-10, 2020

40. N. Passalis, A. Tefas, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data”, Pattern Recognition Letters, vol.136, 183-189,  2020

41. A. Ntakaris, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators”, PLoS ONE, e0234107, DOI: 10.1371/journal.pone.0234107, 2020

42. J. Arje, C. Melvad, M.R. Jeppesen, S.A. Madsen, J. Raitoharju, M.S. Rasmussen, A. Iosifidis, V. Tirronen, M. Gabbouj, K. Meissner and T.T. Hoye, “Automatic image-based identification and biomass estimation if invertebrates”, Methods in Ecology and Evolution, vol. 1, no. 8, pp. 922-931, 2020 

43. A. Tsantekidis, N. Passalis, A. Tefas, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Using Deep Learning for price prediction by exploiting stationary limit order book features”, Applied Soft Computing, accepted May 2020 

44. M Krestenitis, N. Passalis, A. Iosifidis, M. Gabbouj and A. Tefas, “Recurrent Bag-of-Features for Visual Information Analysis”, Pattern Recognition, accepted March 2020

45. N. Passalis, A. Tefas, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Deep Adaptive Input Normalization for Time Series Forecasting”, IEEE Transactions on Neural Networks and Learning Systems, vol. 3, no. 9, pp. 3760-3765, 2020

46. S. Kiranyaz, T. Ince, A. Iosifidis and M. Gabbouj, “Operational Neural Networks”, Neural Computing and Applications, vol. 32, pp. 6645–6668, 2020 

47. N. Passalis, A. Iosifidis, M. Gabbouj and A. Tefas, “Variance-preserving Deep Metric Learning for Content-based Image Retrieval”, Pattern Recognition Letters, vol. 131, pp. 8-14, 2020

48. D.T. Tran, S. Kiarnyaz, M. Gabbouj and A. Iosifidis, "Heterogeneous Multilayer Generalized Operational Perceptron", IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 3, pp. 710-724 , 2020

49. O.L.P. Hansen, J.C. Svenning, K. Olsen, S. Dupont, B.H. Garner, A. Iosifidis, B.W. Price, T.T. Høye, “Species-level image classification with convolutional neural network enable insect identification from habitus images”, Ecology and Evolution,  DOI: 10.1002/ece3.5921, 2019

50. D.T. Tran, S. Kiranyaz, M. Gabbouj and A. Iosifidis, “Progressive Operational Perceptrons with Memory”, Neurocomputing, vol. 379, pp. 172-181, 2019 

51. A. Ntakaris, G. Mirone, J. Kanniainen, M. Gabbouj and A. Iosifidis, "Feature Engineering for Mid-Price Prediction with Deep Learning", IEEE Access, vol. 7, pp. 82390 – 82412, 2019

52. M. Makinen, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Forecasting of Jump Arrivals in Stock Prices: New Attention-based Network Architecture using Limit Order Book Data”, Quantitative Finance, vol. 19, no. 12, pp. 2033-2050, 2019

53. D.T. Tran, S. Kiranyaz, M. Gabbouj and A. Iosifidis, “PyGOP: A Python Library for Generalized Operational Perceptron”, Knowledge-Based Systems, Volume 182, 104801, 15 October 2019

54. P. Nousi, A. Tsantekidis, N. Passalis, A. Ntakaris, J. Kanniainen, A. Tefas, M. Gabbouj and A. Iosifidis, "Machine Learning for Forecasting Mid Price Movement using Limit Order Book Data", IEEE Access, vol. 7, pp. 64722-64736, 2019

55. N. Passalis, A. Tefas, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Temporal Bag-of-Features Learning for Predicting Mid Price Movements using High Frequency Limit Order Book Data”, IEEE Transactions on Emerging Topics in Computational Intelligence, (Early Access) DOI: 10.1109/TETCI.2018.2872598, 2019

56. D.T. Tran, A. Iosifidis, J. Kanniainen and M. Gabbouj, “Temporal Attention augmented Bilinear Network for Financial Time-Series Data Analysis”, IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 5, pp. 1407-1418, 2019

57. A. Ntakaris, M. Magris, J. Kanniainen, M. Gabbouj and A. Iosifidis, “Benchmark Dataset for Mid-Price Prediction of Limit Order Book data”, Journal of Forecasting, DOI:10.1002/for.2543, 2018

58. J. Raitoharju, E. Riabchenko, I. Ahmad, A. Iosifidis, M. Gabbouj, S. Kiranyaz, V. Torronen, J. Arje, S. Karkkainen and K. Meissner, “Benchmark Database for Find-Grained Image Classification of Benthic Macroinvertebrates”, Image and Vision Computing, vol. 78, pp. 73-83, 2018

59. D.T. Tran, A. Iosifidis and M. Gabbouj, “Improving Efficiency in Convolutional Neural Network with Multilinear Filters”, accepted in Neural Networks journal, vol. 105, pp. 328-339, 2018

60. G. Cao, A. Iosifidis, K. Chen and M. Gabbouj, “Generalized Multi-view Embedding for Visual Recognition and Cross-modal Retrieval”, IEEE Transactions on Cybernetics, vol. 48, no. 9, pp. 2542-2555, 2018

61. C. Aytekin, A. Iosifidis and M. Gabbouj, “Probabilistic Saliency Estimation”, Pattern Recognition, vol. 74, pp. 359-372, 2018

62. G. Cao, A. Iosifidis and M. Gabbouj, “Neural Class-Specific Regression for Face Verification”, IET Biometrics, vol. 7, no. 1, pp. 63-70, 2018

63. V. Mygdalis, A. Iosifidis, A. Tefas and I. Pitas, “Semi-Supervised Subclass Support Vector Data Description for Image and Video Classification”, Neurocomputing, vol. 278, pp. 51-61, 2018 (Corrigendum vol. 291, pp. 237-241, 2018)

64. D.T. Tran, M. Gabbouj and A. Iosifidis, “Multilinear Class-Specific Discriminant Analysis”, Pattern Recognition Letters, vol. 100, pp. 131-136, 2017

65. G. Cao, A. Iosifidis and M. Gabbouj, “Multi-view Nonparametric Discriminant Analysis for Image Retrieval and Recognition”, IEEE Signal Processing Letters, vol. 24, no. 10, pp. 1537-1541, 2017

66. A. Iosifidis and M. Gabbouj, “Class-Specific Kernel Discriminant Analysis revisited: further analysis and extensions”, IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4485-4496, 2017

67. M.A. Waris, A. Iosifidis and M. Gabbouj, “CNN-based Edge Filtering for Object Proposals”, Neurocomputing, vol. 266, pp. 631-640, 2017

68. S. Kaveh, A. Iosifidis and M. Gabbouj, “On the comparison of random and Hebbian weights for the training of single-hidden layer feedforward neural networks”, Expert Systems with Application, vol. 83, pp. 177-186, 2017

69. C. Aytekin, A. Iosifidis and M. Gabbouj, “'Learning Graph Affinities for Spectral Graph-based Salient Object Detection”, Pattern Recognition, vol. 64, pp. 159-167, 2017

70. S. Kiranyaz, T. Ince, A. Iosifidis and M. Gabbouj, “Progressive Operational Perceptrons”, Neurocomputing, vol. 224, pp. 142-154, 2017

71. J. Arje, S. Karkkainen, K. Meissner, A. Iosifidis, T. Ince, M. Gabbouj and S. Kiranyaz, “The effect of automated taxa identification errors on biological indices”, Expert Systems with Applications, vol. 72, pp. 108-120, 2017

72. A. Iosifidis, A. Tefas and I. Pitas, “Approximate Kernel Extreme Learning Machine for Large-Scale Data Classification”, Neurocomputing, vol. 219, pp. 210-220, 2017

73. A. Iosifidis, V. Mygdalis, A. Tefas and I. Pitas, “One-Class Classification based on Extreme Learning and Geometric Class Information”, Neural Processing Letters, vol. 45, pp. 577-592, 2017

74. A. Iosifidis and M. Gabbouj, “Scaling up Class-Specific Kernel Discriminant Analysis for large-scale Face Verification”, IEEE Transactions on Information Forensics and Security, vol. 11, no. 11, pp. 2453-2465, 2016

75. V. Mygdalis, A. Iosifidis, A. Tefas and I. Pitas, “Graph Embedded One-Class Classifiers for media data classification”, Pattern Recognition, vol. 60, pp. 585-595, 2017

76. A. Iosifidis and M. Gabbouj, “Nyström-based Approximate Kernel Subspace Learning”, Pattern Recognition, vol. 57, pp. 190-197, 2016

77. F. Patrona, A. Iosifidis, A. Tefas and I. Pitas, “Visual Voice Activity Detection in the Wild”, IEEE Transactions on Multimedia, vol. 18, no. 6, pp. 967-977, 2016

78. A. Iosifidis and M. Gabbouj, “Multi-class Support Vector Machine Classifiers using Intrinsic and Penalty Graphs”, Pattern Recognition, vol. 55, pp. 231-246, 2016

79. A. Iosifidis, A. Tefas and I. Pitas, “Graph Embedded Extreme Learning Machine”, IEEE Transactions on Cybernetics, vol. 46, no. 1, pp. 311-324, 2016

80. C. Aytekin, S. Kiranyaz, A. Iosifidis and M. Gabbouj, “Recent Advances in Salient Object Detection – Towards Object Recognition in Big Media Data”, Futura – Big Data, vol. 35, no. 2, pp. 80-92, 2016

81. A. Iosifidis and M. Gabbouj, “On the kernel Extreme Learning Machine speedup”, Pattern Recognition Letters, vol. 68, pp. 205-210, 2015

82. A. Iosifidis, A. Tefas and I. Pitas, “Class-specific Reference Discriminant Analysis with application in Human Behavior Analysis”, IEEE Transactions on Human-Machine Systems, vol. 45, no. 3, 315-326, 2015

83. A. Iosifidis, “Extreme Learning Machine based Supervised Subspace Learning”, Neurocomputing, vol. 167, pp. 158-164, 2015

84. A. Iosifidis, A. Tefas and I. Pitas, “Sparse Extreme Learning Machine classifier exploiting Intrinsic Graphs”, Pattern Recognition Letters, vol. 65, pp. 192-196, 2015

85. I. Mademlis, A. Iosifidis, A. Tefas, N. Nikolaidis and I. Pitas, “Exploiting Stereoscopic Disparity for Augmenting Human Activity Recognition Performance”, Multimedia Tools & Applications, vol. 75, pp. 11641-11660, 2016

86. A. Iosifidis, A. Tefas and I. Pitas, “DropELM: Fast Neural Network Regularization with Dropout and DropConnect”, Neurocomputing, vol. 162, pp. 57-66, 2015

87. A. Iosifidis, A. Tefas and I. Pitas, “Distance-based Human Action Recognition using optimized class representations”, Neurocomputing, vol. 161, pp. 47-55, 2015

88. A. Iosifidis, A. Tefas and I. Pitas, “On the Kernel Extreme Learning Machine Classifier”, Pattern Recognition Letters, vol. 54, pp. 11-17, 2015

89. A. Iosifidis, E. Marami, A. Tefas, I. Pitas and K. Lyroudia, “The MOBISERV-AIIA Eating and Drinking multi-view database for vision-based assisted living”, Journal of Information Hiding and Multimedia Signal Processing, vol. 6, no. 2, pp. 254-273, 2015

90. A. Iosifidis, A. Tefas and I. Pitas, “Human Action Recognition based on Multi-view Regularized Extreme Learning Machine”, International Journal on Artificial Intelligence Tools, 2015

91. A. Iosifidis, A. Tefas and I. Pitas, “Kernel Reference Discriminant Analysis”, Pattern Recognition Letters, vol. 49, pp. 85-91, 2014

92. A. Iosifidis, A. Tefas and I. Pitas, “Discriminant Bag of Words based Representation for Human Action Recognition”, Pattern Recognition Letters, vol. 49, pp. 185-192, 2014

93. A. Iosifidis, A. Tefas and I. Pitas, “Regularized Extreme Learning Machine for Multi-view Semi-supervised Action Recognition”, Neurocomputing, vol. 145, pp. 250-262, 2014

94. A. Iosifidis, A. Tefas and I. Pitas, “Multidimensional Sequence Classification based on Fuzzy Distances and Discriminant Analysis”, IEEE Transactions on Knowledge and Data Engineering, vol. 93, no. 6, pp. 1445-1457, 2013

95. A. Iosifidis, A. Tefas and I. Pitas, “Minimum Class Variance Extreme Learning Machine for Human Action Recognition”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 11, pp. 1968-1979, 2013

96. A. Iosifidis, A. Tefas and I. Pitas, “Dynamic action recognition based on Dynemes and Extreme Learning Machine”, Pattern Recognition Letters, vol. 34, pp. 1890-1898, 2013

97. A. Iosifidis, A. Tefas and I. Pitas, “Learning sparse representations for view-independent human action recognition based on fuzzy distances”, Neurocomputing, vol. 121, pp. 334-353, 2013

98. A. Iosifidis, A. Tefas and I. Pitas, “On the optimal class representation in Linear Discriminant Analysis”, IEEE Transactions on Neural Networks and Learning Systems, vol. 24, no. 9, pp. 1491-1497, 2013

99. A. Iosifidis, A. Tefas and I. Pitas, "Multi-view Action Recognition Based on Action Volumes, Fuzzy Distances and Cluster Discriminant Analysis", Signal Processing, vol. 93, pp. 1445-1457, 2013

100. A. Iosifidis, A. Tefas and I. Pitas, "View-invariant action recognition based on Artificial Neural Networks", IEEE Transactions on Neural Networks and Learning Systems, vol. 23, no. 3, pp. 412-424, 2012

101. A. Iosifidis, A. Tefas, N. Nikolaidis and I. Pitas, "Multi-view Human Movement Recognition based on Fuzzy Distances and Linear Discriminant Analysis", Computer Vision & Image Understanding, vol. 116, pp. 347-360, 2012

102. A. Iosifidis, A. Tefas and I. Pitas, "Activity based Person Identification using Fuzzy Representation and Discriminant Learning", IEEE Transactions on Information Forensics and Security, vol. 7, no. 2, pp. 530-542, 2012

103. A. Iosifidis, S.G. Mouroutsos and A. Gasteratos, “A hybrid static/active video surveillance system”, International Journal of Optomechatronics, vol. 5, no. 1, pp. 80-95, 2011