Xing Lin
Xing Lin
Research Scientist, Tsinghua Univ.; Postdocs, UCLA, Stanford; PhD, Tsinghua; Visiting Student, MIT
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Cited by
Cited by
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
Spatial-spectral encoded compressive hyperspectral imaging
X Lin, Y Liu, J Wu, Q Dai
ACM Transactions on Graphics (TOG) 33 (6), 1-11, 2014
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
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
Dual-coded compressive hyperspectral imaging
X Lin, G Wetzstein, Y Liu, Q Dai
Optics letters 39 (7), 2044-2047, 2014
Camera array based light field microscopy
X Lin, J Wu, G Zheng, Q Dai
Biomedical optics express 6 (9), 3179-3189, 2015
Coded focal stack photography
X Lin, J Suo, G Wetzstein, Q Dai, R Raskar
IEEE International Conference on Computational Photography (ICCP), 1-9, 2013
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
Transparent object reconstruction via coded transport of intensity
C Ma, X Lin, J Suo, Q Dai, G Wetzstein
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014
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
Snapshot hyperspectral volumetric microscopy
J Wu, B Xiong, X Lin, J He, J Suo, Q Dai
Scientific reports 6 (1), 1-10, 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
Robust and accurate transient light transport decomposition via convolutional sparse coding
X Hu, Y Deng, X Lin, J Suo, Q Dai, C Barsi, R Raskar
Optics letters 39 (11), 3177-3180, 2014
Recovering scene geometry under wavy fluid via distortion and defocus analysis
M Zhang, X Lin, M Gupta, J Suo, Q Dai
European Conference on Computer Vision, 234-250, 2014
Coded aperture pair for quantitative phase imaging
J Wu, X Lin, Y Liu, J Suo, Q Dai
Optics letters 39 (19), 5776-5779, 2014
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
Separable coded aperture for depth from a single image
J Lin, X Lin, X Ji, Q Dai
IEEE Signal Processing Letters 21 (12), 1471-1475, 2014
Extracting depth and radiance from a defocused video pair
X Lin, J Suo, Q Dai
IEEE Transactions on Circuits and Systems for Video Technology 25 (4), 557-569, 2014
Iterative feedback estimation of depth and radiance from defocused images
X Lin, J Suo, X Cao, Q Dai
Asian Conference on Computer Vision, 95-109, 2012
Response to Comment on" All-optical machine learning using diffractive deep neural networks"
D Mengu, Y Luo, Y Rivenson, X Lin, M Veli, A Ozcan
arXiv preprint arXiv:1810.04384, 2018
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