A needle-based deep-neural-network camera

11/14/2020
by   Ruipeng Guo, et al.
8

We experimentally demonstrate a camera whose primary optic is a cannula (diameter=0.22mm and length=12.5mm) that acts a lightpipe transporting light intensity from an object plane (35cm away) to its opposite end. Deep neural networks (DNNs) are used to reconstruct color and grayscale images with field of view of 180 and angular resolution of  0.40. When trained on images with depth information, the DNN can create depth maps. Finally, we show DNN-based classification of the EMNIST dataset without and with image reconstructions. The former could be useful for imaging with enhanced privacy.

READ FULL TEXT

page 2

page 3

page 4

page 5

page 6

research
02/22/2017

Lensless computational imaging through deep learning

Deep learning has been proven to yield reliably generalizable answers to...
research
11/10/2020

Classification of optics-free images with deep neural networks

The thinnest possible camera is achieved by removing all optics, leaving...
research
05/09/2018

Deep 2.5D Vehicle Classification with Sparse SfM Depth Prior for Automated Toll Systems

Automated toll systems rely on proper classification of the passing vehi...
research
12/26/2018

A Unified Learning Based Framework for Light Field Reconstruction from Coded Projections

Light field presents a rich way to represent the 3D world by capturing t...
research
12/01/2019

DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction

Deep Neural Networks (DNNs) have the potential to improve the quality of...
research
12/14/2019

Sensor-Independent Illumination Estimation for DNN Models

While modern deep neural networks (DNNs) achieve state-of-the-art result...
research
05/23/2022

Novel Light Field Imaging Device with Enhanced Light Collection for Cold Atom Clouds

We present a light field imaging system that captures multiple views of ...

Please sign up or login with your details

Forgot password? Click here to reset