Ternausnet: U-net with vgg11 encoder pre-trained on imagenet for image segmentation V Iglovikov, A Shvets arXiv preprint arXiv:1801.05746, 2018 | 726 | 2018 |
Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning VII Alexey A Shvets, Alexander Rakhlin, Alexandr A Kalinin 2018 17th IEEE International Conference on Machine Learning and Applications …, 2018 | 407 | 2018 |
Deep convolutional neural networks for breast cancer histology image analysis A Rakhlin, A Shvets, V Iglovikov, AA Kalinin Image Analysis and Recognition: 15th International Conference, ICIAR 2018 …, 2018 | 381 | 2018 |
Pediatric bone age assessment using deep convolutional neural networks V Iglovikov, A Rakhlin, A Kalinin, A Shvets Deep Learning in Medical Image Analysis (DLMIA) Workshop, 2017 | 232 | 2017 |
Fully Convolutional Network for Automatic Road Extraction from Satellite Imagery A Buslaev, SS Seferbekov, VI Iglovikov, AA Shvets 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition …, 2018 | 199 | 2018 |
Feature Pyramid Network for Multi-Class Land Segmentation S Seferbekov, V Iglovikov, A Buslaev, AA Shvets 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition …, 2018 | 187 | 2018 |
TernausNetV2: Fully Convolutional Network for Instance Segmentation V Iglovikov, S Seferbekov, A Buslaev, A Shvets 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition …, 2018 | 183 | 2018 |
2017 robotic instrument segmentation challenge M Allan, A Shvets, T Kurmann, Z Zhang, R Duggal, YH Su, N Rieke, ... arXiv preprint arXiv:1902.06426, 2019 | 130 | 2019 |
CD45 functions as a signaling gatekeeper in T cells AH Courtney, AA Shvets, W Lu, G Griffante, M Mollenauer, V Horkova, ... Science signaling 12 (604), eaaw8151, 2019 | 119 | 2019 |
Angiodysplasia Detection and Localization Using Deep Convolutional Neural Networks AA Shvets, VI Iglovikov, A Rakhlin, AA Kalinin 2018 17th IEEE International Conference on Machine Learning and Applications …, 2018 | 91 | 2018 |
Ternausnet: U-net with vgg11 encoder pre-trained on imagenet for image segmentation. arXiv 2018 V Iglovikov, A Shvets arXiv preprint arXiv:1801.05746, 0 | 82 | |
Theory of colloid depletion stabilization by unattached and adsorbed polymers AN Semenov, AA Shvets Soft Matter 11 (45), 8863-8878, 2015 | 60 | 2015 |
Medical image segmentation using deep neural networks with pre-trained encoders AA Kalinin, VI Iglovikov, A Rakhlin, AA Shvets Deep learning applications, 39-52, 2020 | 57 | 2020 |
Deep learning approaches for understanding simple speech commands RA Solovyev, M Vakhrushev, A Radionov, II Romanova, AA Amerikanov, ... 2020 IEEE 40th international conference on electronics and nanotechnology …, 2020 | 49 | 2020 |
Robotic instrument segmentation challenge M Allan, A Shvets, T Kurmann, Z Zhang, R Duggal, YH Su, N Rieke, ... arXiv preprint arXiv:1902.06426 2017, 1-14, 2017 | 47 | 2017 |
Mechanisms of protein search for targets on DNA: theoretical insights AA Shvets, MP Kochugaeva, AB Kolomeisky Molecules 23 (9), 2106, 2018 | 44 | 2018 |
Crowding on DNA in protein search for targets AA Shvets, AB Kolomeisky The journal of physical chemistry letters 7 (13), 2502-2506, 2016 | 39 | 2016 |
Sequence heterogeneity accelerates protein search for targets on DNA AA Shvets, AB Kolomeisky The Journal of chemical physics 143 (24), 2015 | 32 | 2015 |
Effective interactions between solid particles mediated by free polymer in solution AA Shvets, AN Semenov The Journal of Chemical Physics 139 (5), 2013 | 32 | 2013 |
Role of static and dynamic obstacles in the protein search for targets on DNA A Shvets, M Kochugaeva, AB Kolomeisky The Journal of Physical Chemistry B 120 (26), 5802-5809, 2016 | 28 | 2016 |