LOEN: Lensless opto-electronic neural network empowered machine vision.

ABSTRACT: Machine vision faces bottlenecks in computing power consumption and large amounts of data. Although opto-electronic hybrid neural networks can provide assistance, they usually have complex structures and are highly dependent on a coherent light source; therefore, they are not suitable for natural lighting environment applications. In this paper, we propose a novel lensless opto-electronic neural network architecture for machine vision applications. The architecture optimizes a passive optical mask by means of a task-oriented neural network design, performs the optical convolution calculation operation using the lensless architecture, and reduces the device size and amount of calculation required. We demonstrate the performance of handwritten digit classification tasks with a multiple-kerne

SUBMITTER: Shi W 

PROVIDER: S-EPMC9068799 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature