Neuromorphic implementation of a software-defined camera that can see through fire and smoke in real-time

Jae H. Cha; A. Lynn Abbott; Harold H. Szu; Jefferson Willey; Joseph Landa; Keith A. Krapels

doi:10.1117/12.2052021

19 June 2014 Neuromorphic implementation of a software-defined camera that can see through fire and smoke in real-time

Jae H. Cha, A. Lynn Abbott, Harold H. Szu, Jefferson Willey, Joseph Landa, Keith A. Krapels

Proceedings Volume 9118, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XII; 911809 (2014) https://doi.org/10.1117/12.2052021
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

Abstract

Software-defined Cameras (SDC) based on Boltzmann’s molecular thermodynamics can “see” through visually-degraded fields such as fire, fog, and dust in some situations. This capability is possible by means of unsupervised learning implemented on a neuromorphic algo-tecture. This paper describes the SDC algorithm design strategy with respect to nontrivial solutions, stability, and accuracy. An example neuromorphic learning algorithm is presented along with unsupervised learning stopping criteria.

Citation Download Citation

Jae H. Cha, A. Lynn Abbott, Harold H. Szu, Jefferson Willey, Joseph Landa, and Keith A. Krapels "Neuromorphic implementation of a software-defined camera that can see through fire and smoke in real-time", Proc. SPIE 9118, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XII, 911809 (19 June 2014); https://doi.org/10.1117/12.2052021

ACCESS THE FULL ARTICLE

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