| All-optical machine learning using diffractive deep neural networks X Lin, Y Rivenson, NT Yardimci, M Veli, Y Luo, M Jarrahi, A Ozcan Science 361 (6406), 1004-1008, 2018 | 1040 | 2018 |
| Phase recovery and holographic image reconstruction using deep learning in neural networks Y Rivenson, Y Zhang, H Günaydın, D Teng, A Ozcan Light: Science & Applications 7 (2), 17141-17141, 2018 | 743 | 2018 |
| Deep learning microscopy Y Rivenson, Z Göröcs, H Günaydin, Y Zhang, H Wang, A Ozcan Optica 4 (11), 1437-1443, 2017 | 560 | 2017 |
| Deep learning enables cross-modality super-resolution in fluorescence microscopy H Wang, Y Rivenson, Y Jin, Z Wei, R Gao, H Günaydın, LA Bentolila, ... Nature methods 16 (1), 103-110, 2019 | 522 | 2019 |
| Virtual histological staining of unlabelled tissue-autofluorescence images via deep learning Y Rivenson, H Wang, Z Wei, K de Haan, Y Zhang, Y Wu, H Günaydın, ... Nature biomedical engineering 3 (6), 466-477, 2019 | 362 | 2019 |
| Roadmap on optical security B Javidi, A Carnicer, M Yamaguchi, T Nomura, E Pérez-Cabré, MS Millán, ... Journal of Optics 18 (8), 083001, 2016 | 359 | 2016 |
| Extended depth-of-field in holographic imaging using deep-learning-based autofocusing and phase recovery Y Wu, Y Rivenson, Y Zhang, Z Wei, H Günaydin, X Lin, A Ozcan Optica 5 (6), 704-710, 2018 | 265 | 2018 |
| PhaseStain: the digital staining of label-free quantitative phase microscopy images using deep learning Y Rivenson, T Liu, Z Wei, Y Zhang, K de Haan, A Ozcan Light: Science & Applications 8 (1), 23, 2019 | 236 | 2019 |
| Compressive fresnel holography Y Rivenson, A Stern, B Javidi Journal of Display Technology 6 (10), 506-509, 2010 | 201 | 2010 |
| Compressive hyperspectral imaging by random separable projections in both the spatial and the spectral domains Y August, C Vachman, Y Rivenson, A Stern Applied optics 52 (10), D46-D54, 2013 | 191 | 2013 |
| Deep learning in holography and coherent imaging Y Rivenson, Y Wu, A Ozcan Light: Science & Applications 8 (1), 85, 2019 | 189 | 2019 |
| Compressed imaging with a separable sensing operator Y Rivenson, A Stern IEEE Signal Processing Letters 16 (6), 449-452, 2009 | 186 | 2009 |
| Deep learning enhanced mobile-phone microscopy Y Rivenson, H Ceylan Koydemir, W Hongda, Z Wei, Z Ren, H Gunaydin, ... arXiv preprint arXiv:1712.04139, 2017 | 165 | 2017 |
| Three-dimensional virtual refocusing of fluorescence microscopy images using deep learning Y Wu, Y Rivenson, H Wang, Y Luo, E Ben-David, LA Bentolila, C Pritz, ... Nature methods 16 (12), 1323-1331, 2019 | 163 | 2019 |
| Overview of compressive sensing techniques applied in holography Y Rivenson, A Stern, B Javidi Applied optics 52 (1), A423-A432, 2013 | 147 | 2013 |
| Speckle denoising in digital holography by nonlocal means filtering A Uzan, Y Rivenson, A Stern Applied optics 52 (1), A195-A200, 2013 | 141 | 2013 |
| A deep learning-enabled portable imaging flow cytometer for cost-effective, high-throughput, and label-free analysis of natural water samples Z Gӧrӧcs, M Tamamitsu, V Bianco, P Wolf, S Roy, K Shindo, K Yanny, ... Light: Science & Applications 7 (1), 66, 2018 | 133 | 2018 |
| Design of task-specific optical systems using broadband diffractive neural networks Y Luo, D Mengu, NT Yardimci, Y Rivenson, M Veli, M Jarrahi, A Ozcan Light: Science & Applications 8 (1), 112, 2019 | 127 | 2019 |
| Analysis of diffractive optical neural networks and their integration with electronic neural networks D Mengu, Y Luo, Y Rivenson, A Ozcan IEEE Journal of Selected Topics in Quantum Electronics 26 (1), 1-14, 2019 | 118 | 2019 |
| Deep learning-based super-resolution in coherent imaging systems T Liu, K De Haan, Y Rivenson, Z Wei, X Zeng, Y Zhang, A Ozcan Scientific reports 9 (1), 1-13, 2019 | 111 | 2019 |
Aydogan OzcanChancellor's Professor at UCLA & HHMI ProfessorZweryfikowany adres z ucla.edu
