| Deep-anomaly: Fully convolutional neural network for fast anomaly detection in crowded scenes M Sabokrou, M Fayyaz, M Fathy, Z Moayed, R Klette Computer Vision and Image Understanding 172, 88-97, 2018 | 221 | 2018 |
| Adversarially learned one-class classifier for novelty detection M Sabokrou, M Khalooei, M Fathy, E Adeli Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 221 | 2018 |
| Deep-cascade: Cascading 3d deep neural networks for fast anomaly detection and localization in crowded scenes M Sabokrou, M Fayyaz, M Fathy, R Klette IEEE Transactions on Image Processing 26 (4), 1992-2004, 2017 | 168 | 2017 |
| Real-time anomaly detection and localization in crowded scenes M Sabokrou, M Fathy, M Hoseini, R Klette Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 131 | 2015 |
| Video anomaly detection and localisation based on the sparsity and reconstruction error of auto-encoder M Sabokrou, M Fathy, M Hoseini Electronics Letters 52 (13), 1122-1124, 2016 | 96 | 2016 |
| Lets keep it simple, using simple architectures to outperform deeper and more complex architectures SH HasanPour, M Rouhani, M Fayyaz, M Sabokrou arXiv preprint arXiv:1608.06037, 2016 | 62 | 2016 |
| Avid: Adversarial visual irregularity detection M Sabokrou, M Pourreza, M Fayyaz, R Entezari, M Fathy, J Gall, E Adeli Asian Conference on Computer Vision, 488-505, 2018 | 42 | 2018 |
| STFCN: spatio-temporal FCN for semantic video segmentation M Fayyaz, MH Saffar, M Sabokrou, M Fathy, R Klette, F Huang arXiv preprint arXiv:1608.05971, 2016 | 34 | 2016 |
| Towards principled design of deep convolutional networks: introducing SimpNet SH Hasanpour, M Rouhani, M Fayyaz, M Sabokrou, E Adeli arXiv preprint arXiv:1802.06205, 2018 | 22 | 2018 |
| Fast and accurate detection and localization of abnormal behavior in crowded scenes M Sabokrou, M Fathy, Z Moayed, R Klette Machine Vision and Applications 28 (8), 965-985, 2017 | 19 | 2017 |
| Online signature verification based on feature representation M Fayyaz, MH Saffar, M Sabokrou, M Hoseini, M Fathy 2015 The International Symposium on Artificial Intelligence and Signal …, 2015 | 19 | 2015 |
| STFCN: spatio-temporal fully convolutional neural network for semantic segmentation of street scenes M Fayyaz, MH Saffar, M Sabokrou, M Fathy, F Huang, R Klette Asian Conference on Computer Vision, 493-509, 2016 | 18 | 2016 |
| Feature representation for online signature verification M Fayyaz, M Hajizadeh_Saffar, M Sabokrou, M Fathy arXiv preprint arXiv:1505.08153, 2015 | 17* | 2015 |
| Self-supervised representation learning via neighborhood-relational encoding M Sabokrou, M Khalooei, E Adeli Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 15 | 2019 |
| Solving heterogeneous coverage problem in Wireless Multimedia Sensor Networks in a dynamic environment using Evolutionary Strategies H Fayyazi, M Sabokrou, M Hosseini, A Sabokrou 2011 1st International eConference on Computer and Knowledge Engineering …, 2011 | 15* | 2011 |
| Driver behavior detection and classification using deep convolutional neural networks M Shahverdy, M Fathy, R Berangi, M Sabokrou Expert Systems with Applications 149, 113240, 2020 | 14 | 2020 |
| A novel approach for Finger Vein verification based on self-taught learning M Fayyaz, M Hajizadeh-Saffar, M Sabokrou, M Hoseini, M Fathy 2015 9th Iranian Conference on Machine Vision and Image Processing (MVIP), 88-91, 2015 | 12 | 2015 |
| Deep end-to-end one-class classifier M Sabokrou, M Fathy, G Zhao, E Adeli IEEE transactions on neural networks and learning systems, 2020 | 10 | 2020 |
| Autoids: auto-encoder based method for intrusion detection system M Gharib, B Mohammadi, SH Dastgerdi, M Sabokrou arXiv preprint arXiv:1911.03306, 2019 | 7 | 2019 |
| End-to-end adversarial learning for intrusion detection in computer networks B Mohammadi, M Sabokrou 2019 IEEE 44th Conference on Local Computer Networks (LCN), 270-273, 2019 | 6 | 2019 |
Mahmood FathyProfessor computer Engineering, Iran university of science and technologyVerified email at iust.ac.ir
