| 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 | 2087 | 2018 |
| Large-scale neuromorphic optoelectronic computing with a reconfigurable diffractive processing unit T Zhou, X Lin, J Wu, Y Chen, H Xie, Y Li, J Fan, H Wu, L Fang, Q Dai Nature Photonics 15 (5), 367–373, 2021 | 576 | 2021 |
| 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 | 382 | 2018 |
| Fourier-space diffractive deep neural network T Yan, J Wu, T Zhou, H Xie, F Xu, J Fan, L Fang, X Lin, Q Dai Physical review letters 123 (2), 023901, 2019 | 341 | 2019 |
| Spatial-spectral encoded compressive hyperspectral imaging X Lin, Y Liu, J Wu, Q Dai ACM Transactions on Graphics (TOG) 33 (6), 1-11, 2014 | 330 | 2014 |
| Computational Snapshot Multispectral Cameras: Toward dynamic capture of the spectral world X Cao, T Yue, X Lin, S Lin, X Yuan, Q Dai, L Carin, D Brady IEEE Signal Processing Magazine 33 (5), 95-108, 2016 | 284 | 2016 |
| In situ optical backpropagation training of diffractive optical neural networks T Zhou, L Fang, T Yan, J Wu, Y Li, J Fan, H Wu, X Lin, Q Dai Photonics Research 8 (6), 940-953, 2020 | 186 | 2020 |
| Iterative tomography with digital adaptive optics permits hour-long intravital observation of 3D subcellular dynamics at millisecond scale J Wu, Z Lu, D Jiang, Y Guo, H Qiao, Y Zhang, T Zhu, Y Cai, X Zhang, ... Cell 184 (12), 3318-3332. e17, 2021 | 183 | 2021 |
| Dual-coded compressive hyperspectral imaging X Lin, G Wetzstein, Y Liu, Q Dai Optics letters 39 (7), 2044-2047, 2014 | 176 | 2014 |
| Camera array based light field microscopy X Lin, J Wu, G Zheng, Q Dai Biomedical optics express 6 (9), 3179-3189, 2015 | 165 | 2015 |
| Reinforcing neuron extraction and spike inference in calcium imaging using deep self-supervised denoising X Li, G Zhang, J Wu, Y Zhang, Z Zhao, X Lin, H Qiao, H Xie, H Wang, ... Nature methods 18 (11), 1395-1400, 2021 | 123 | 2021 |
| Unsupervised content-preserving transformation for optical microscopy X Li, G Zhang, H Qiao, F Bao, Y Deng, J Wu, Y He, J Yun, X Lin, H Xie, ... Light: Science & Applications 10 (1), 44, 2021 | 111 | 2021 |
| Analog optical computing for artificial intelligence J Wu, X Lin, Y Guo, J Liu, L Fang, S Jiao, Q Dai Engineering 10, 133-145, 2022 | 97 | 2022 |
| Label-free bioaerosol sensing using mobile microscopy and deep learning Y Wu, A Calis, Y Luo, C Chen, M Lutton, Y Rivenson, X Lin, HC Koydemir, ... ACS Photonics 5 (11), 4617-4627, 2018 | 83 | 2018 |
| Residual D2NN: training diffractive deep neural networks via learnable light shortcuts H Dou, Y Deng, T Yan, H Wu, X Lin, Q Dai Optics Letters 45 (10), 2688-2691, 2020 | 76 | 2020 |
| Coded focal stack photography X Lin, J Suo, G Wetzstein, Q Dai, R Raskar IEEE International Conference on Computational Photography (ICCP), 1-9, 2013 | 72 | 2013 |
| All-optical graph representation learning using integrated diffractive photonic computing units T Yan, R Yang, Z Zheng, X Lin, H Xiong, Q Dai Science Advances 8 (24), abn7630, 2022 | 70 | 2022 |
| Snapshot hyperspectral volumetric microscopy J Wu, B Xiong, X Lin, J He, J Suo, Q Dai Scientific reports 6 (1), 24624, 2016 | 67 | 2016 |
| Computational optical sectioning with an incoherent multiscale scattering model for light-field microscopy Y Zhang, Z Lu, J Wu, X Lin, D Jiang, Y Cai, J Xie, Y Wang, T Zhu, X Ji, ... Nature communications 12 (1), 6391, 2021 | 58 | 2021 |
| Optical multi-task learning using multi-wavelength diffractive deep neural networks Z Duan, H Chen, X Lin Nanophotonics, 2023 | 44 | 2023 |
Qionghai DaiTsinghua Universitytsinghua.edu.cn의 이메일 확인됨
