Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Reduce Computational Complexity! Inspiration from Flies

Not Accessible

Your library or personal account may give you access

Abstract

Inspired by the clustered typologies of arthropod corneal nanostructures, we study optical preprocessing. We use topological defects to enhance optical encoders. These encoders enable shallow neural networks to process visual data with reduced computational complexity.

© 2021 The Author(s)

PDF Article  |   Presentation Video
More Like This
Bioinspired, multi-scale photonic-crystal films for hybrid polarimetric imaging and sensing

Ji Feng, Xiaojing Weng, Miguel A.G. Mandujano, Eugenio R. Méndez, Yadong Yin, and Luat T. Vuong
JW5Q.4 CLEO: Applications and Technology (CLEO:A&T) 2022

Neuro-inspired Computing: From Resistive Memory to Optics

Charles Mackin, Pritish Narayanan, Hsinyu Tsai, Stefano Ambrogio, An Chen, and Geoffrey W. Burr
ce_3_3 The European Conference on Lasers and Electro-Optics (CLEO/Europe) 2019

Data Augmentation to Reduce Computational Complexity of Neural-Network-Based Soft-Failure Cause Identifier

Lareb Zar Khan, Pedro J. Freire, João Pedro, Nelson Costa, Antonio Napoli, and Nicola Sambo
M3G.3 Optical Fiber Communication Conference (OFC) 2023

Presentation Video

Presentation video access is available to:

  1. Optica Publishing Group subscribers
  2. Technical meeting attendees
  3. Optica members who wish to use one of their free downloads. Please download the article first. After downloading, please refresh this page.

Contact your librarian or system administrator
or
Log in to access Optica Member Subscription or free downloads


More Like This
Bioinspired, multi-scale photonic-crystal films for hybrid polarimetric imaging and sensing

Ji Feng, Xiaojing Weng, Miguel A.G. Mandujano, Eugenio R. Méndez, Yadong Yin, and Luat T. Vuong
JW5Q.4 CLEO: Applications and Technology (CLEO:A&T) 2022

Neuro-inspired Computing: From Resistive Memory to Optics

Charles Mackin, Pritish Narayanan, Hsinyu Tsai, Stefano Ambrogio, An Chen, and Geoffrey W. Burr
ce_3_3 The European Conference on Lasers and Electro-Optics (CLEO/Europe) 2019

Data Augmentation to Reduce Computational Complexity of Neural-Network-Based Soft-Failure Cause Identifier

Lareb Zar Khan, Pedro J. Freire, João Pedro, Nelson Costa, Antonio Napoli, and Nicola Sambo
M3G.3 Optical Fiber Communication Conference (OFC) 2023

Manifold Learning for Reducing the Design Complexity of Photonic Nanostructures

Mohammadreza Zandehshahvar, Yashar Kiarashi, Muliang Zhu, Hossein Maleki, Tyler Brown, and Ali Adibi
JTu3A.115 CLEO: Applications and Technology (CLEO:A&T) 2021

Progress in neuro-inspired photonic computing

Satoshi Sunada
12p_N404_9 JSAP-OSA Joint Symposia (JSAP) 2021

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.