1.1k citations · 2.1k across the 9 of their papers we have counts for
13 papers · 1 filter
Cross-modality deep learning brings bright-field microscopy contrast to holography
Yichen Wu, Yilin Luo, Gunvant Chaudhari +4
Deep learning brings bright-field microscopy contrast to holographic images of a sample volume, bridging the volumetric imaging capability of holography with the speckle- and artif…
Deep learning enables high-throughput analysis of particle-aggregation-based bio-sensors imaged using holography
Yichen Wu, Aniruddha Ray, Qingshan Wei +5
Aggregation-based assays, using micro- and nano-particles have been widely accepted as an efficient and cost-effective bio-sensing tool, particularly in microbiology, where particl…
Deep learning-based super-resolution in coherent imaging systems
Tairan Liu, Kevin de Haan, Yair Rivenson +4
We present a deep learning framework based on a generative adversarial network (GAN) to perform super-resolution in coherent imaging systems. We demonstrate that this framework can…
Response to Comment on "All-optical machine learning using diffractive deep neural networks"
Deniz Mengu, Yi Luo, Yair Rivenson +3
In their Comment, Wei et al. (arXiv:1809.08360v1 [cs.LG]) claim that our original interpretation of Diffractive Deep Neural Networks (D2NN) represent a mischaracterization of the s…
Analysis of Diffractive Optical Neural Networks and Their Integration with Electronic Neural Networks
Deniz Mengu, Yi Luo, Yair Rivenson +1
Optical machine learning offers advantages in terms of power efficiency, scalability and computation speed. Recently, an optical machine learning method based on Diffractive Deep N…
Accurate color imaging of pathology slides using holography and absorbance spectrum estimation of histochemical stains
Yibo Zhang, Tairan Liu, Yujia Huang +6
Holographic microscopy presents challenges for color reproduction due to the usage of narrow-band illumination sources, which especially impacts the imaging of stained pathology sl…