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Stanislav I. Protasov
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2020 – today
- 2023
- [j5]Bader Rasheed, Asad Masood Khattak, Adil Khan, Stanislav I. Protasov, Muhammad Ahmad:
Boosting Adversarial Training Using Robust Selective Data Augmentation. Int. J. Comput. Intell. Syst. 16(1): 89 (2023) - [j4]Marina O. Lisnichenko, Stanislav I. Protasov:
Quantum image representation: a review. Quantum Mach. Intell. 5(1): 1-12 (2023) - [j3]Stanislav I. Protasov, Marina O. Lisnichenko:
Faster quantum state decomposition with Tucker tensor approximation. Quantum Mach. Intell. 5(2): 1-10 (2023) - 2022
- [i3]Marina O. Lisnichenko, Stanislav I. Protasov:
Case study on quantum convolutional neural network scalability. CoRR abs/2207.07160 (2022) - 2021
- [j2]Stanislav I. Protasov, Adil Mehmood Khan:
Using Proximity Graph Cut for Fast and Robust Instance-Based Classification in Large Datasets. Complex. 2021: 2011738:1-2011738:9 (2021)
2010 – 2019
- 2018
- [j1]Stanislav I. Protasov, Adil Mehmood Khan, Konstantin Sozykin, Muhammad Ahmad:
Using deep features for video scene detection and annotation. Signal Image Video Process. 12(5): 991-999 (2018) - [c3]Konstantin Sozykin, Stanislav I. Protasov, Adil Khan, Rasheed Hussain, Jooyoung Lee:
Multi-label Class-imbalanced Action Recognition in Hockey Videos via 3D Convolutional Neural Networks. SNPD 2018: 146-151 - 2017
- [i2]Muhammad Ahmad, Stanislav I. Protasov, Adil Mehmood Khan:
Hyperspectral Band Selection Using Unsupervised Non-Linear Deep Auto Encoder to Train External Classifiers. CoRR abs/1705.06920 (2017) - [i1]Konstantin Sozykin, Adil Mehmood Khan, Stanislav I. Protasov, Rasheed Hussain:
Multi-label Class-imbalanced Action Recognition in Hockey Videos via 3D Convolutional Neural Networks. CoRR abs/1709.01421 (2017) - 2016
- [c2]Muhammad Ahmad, Adil Mehmood Khan, Joseph Alexander Brown, Stanislav I. Protasov, Asad Masood Khattak:
Gait fingerprinting-based user identification on smartphones. IJCNN 2016: 3060-3067 - [c1]Muhammad Ahmad, Adil Mehmood Khan, Rasheed Hussain, Stanislav I. Protasov, Francis Chow, Asad Masood Khattak:
Unsupervised geometrical feature learning from hyperspectral data. SSCI 2016: 1-6
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