| Real-time human activity recognition from accelerometer data using Convolutional Neural Networks A Ignatov Applied Soft Computing 62, 915-922, 2018 | 131 | 2018 |
| DSLR-quality photos on mobile devices with deep convolutional networks A Ignatov, N Kobyshev, R Timofte, K Vanhoey, L Van Gool Proceedings of the IEEE International Conference on Computer Vision, 3277-3285, 2017 | 104 | 2017 |
| Ai benchmark: Running deep neural networks on android smartphones A Ignatov, R Timofte, W Chou, K Wang, M Wu, T Hartley, L Van Gool Proceedings of the European Conference on Computer Vision (ECCV), 0-0, 2018 | 81 | 2018 |
| WESPE: weakly supervised photo enhancer for digital cameras A Ignatov, N Kobyshev, R Timofte, K Vanhoey, L Van Gool Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 53 | 2018 |
| Human activity recognition using quasiperiodic time series collected from a single tri-axial accelerometer AD Ignatov, VV Strijov Multimedia tools and applications 75 (12), 7257-7270, 2016 | 49 | 2016 |
| PIRM challenge on perceptual image enhancement on smartphones: report A Ignatov, R Timofte, T Van Vu, T Minh Luu, T X Pham, C Van Nguyen, ... Proceedings of the European Conference on Computer Vision (ECCV), 0-0, 2018 | 30 | 2018 |
| Decision stream: Cultivating deep decision trees D Ignatov, A Ignatov 2017 IEEE 29th International Conference on Tools with Artificial …, 2017 | 9 | 2017 |
| NTIRE 2019 Challenge on Image Enhancement: Methods and Results A Ignatov, R Timofte Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 5 | 2019 |
| AI Benchmark: All About Deep Learning on Smartphones in 2019 A Ignatov, R Timofte, A Kulik, S Yang, K Wang, F Baum, M Wu, L Xu, ... arXiv preprint arXiv:1910.06663, 2019 | 2 | 2019 |
| Replacing Mobile Camera ISP with a Single Deep Learning Model A Ignatov, L Van Gool, R Timofte arXiv preprint arXiv:2002.05509, 2020 | | 2020 |
