Dr. Farshid Ashtiani Profile

Dr. Farshid Ashtiani

at Nokia Bell Labs

SPIE Involvement:

Author

Publications (1)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 17 March 2023 Presentation + Paper

Direct image classification using an on-chip photonic deep neural network

Farshid Ashtiani, Alexander Geers, Firooz Aflatouni

Proceedings Volume 12424, 124240K (2023) https://doi.org/10.1117/12.2655383

KEYWORDS: Integrated photonics, Silicon photonics, Neural networks, Optical signal processing

Read Abstract +

Artificial neural networks have been a major driving force in a wide variety of technologies from pattern recognition and natural language reprocessing to medical diagnosis. Neural networks can be trained to perform a certain set of tasks and are typically formed by the interconnection of multiple layers of neurons to perform linear and nonlinear computations. Highly reconfigurable clock-based digital signal processors have been the main hardware platform to implement such networks. However, clock frequency and memory access time are two main contributors in limiting the processing speed. Integrated photonics benefits from the large available bandwidth at optical frequencies and low-loss interconnects, and has proved to be a promising candidate to address the challenges of electronic systems. Most of the demonstrated photonic neural networks have been either using bench-top setups, or the partial integration of some of the linear and/or nonlinear computation blocks. A scalable solution that can integrate all computation blocks has been an open problem. Here, we demonstrate the first end-to-end photonic deep neural network (PDNN) for direct image classification. On-chip image formation of the target object using a 2D array of grating couplers and direct processing of the received optical signals through linear (optical) and nonlinear (opto-electronic) computation, enable an end-to-end classification time of 570 ps. Using a uniformly distributed supply light enables scaling the PDNN to networks with more layers of neurons. The PDNN chip is used to demonstrate classification of 2- and 4-class datasets of handwritten letters and the system achieves accuracies higher than 93.8% and 89.8%, respectively.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years