Monthly Archives: November 2017

Deep learning microscopy

This week a new paper by the group leaded by A. Ozcan appeared in Optica. Deep learning microscopy, Y. Ribenson et al, at Optica (featured image exctracted from Fig. 6 of the supplement) Abstract, We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field of view and depth of field. After

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Imaging through glass diffusers using densely connected convolutional networks

I just found a new paper by the group of G. Barbastathis at MIT. Imaging through glass diffusers using densely connected convolutional networks, S. Li et al, Submitted on 18 Nov 2017, https://arxiv.org/abs/1711.06810 (featured image from Fig. 3 of the manuscript) Abstract, Computational imaging through scatter generally is accomplished by first characterizing the scattering medium so that its forward operator is obtained;

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Experimental comparison of single-pixel imaging algorithms

I just read on ArXiv.org that L. Bian and his colleagues made a cool comparison between several ways of performing single-pixel imaging. They have tested the performance on several recovery procedures, some quite familiar but others not so well stablished. I find both Table 1 and Fig. 7 extremely interesting. One sums up really well the different reconstruction approaches that can

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Toward Depth Estimation Using Mask-Based Lensless Cameras

I just discovered on ArXiv.org a new paper by M. Asif, one of the guys behind the FlatCam. Toward Depth Estimation Using Mask-Based Lensless Cameras, M. Asif, submitted November 9th, http://arxiv.org/abs/1711.03527 (featured image extracted from Fig.1 of the manuscript) Abstract: Recently, coded masks have been used to demonstrate a thin form-factor lensless camera, FlatCam, in which a mask is placed immediately on

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