Neuromorphic Implementation of a Software-defined Camera that can "See" through Fire and Dust in Real-time

被引：0
|
作者：
Cha, Jae H. [1 ]
Abbott, A. Lynn [1 ]
Szu, Harold H. [2 ]
Willey, Jefferson [2 ]
Landa, Joseph [2 ]
Krapels, Keith A. [3 ]
机构：
[1] Virginia Polytech Inst & State Univ, Blacksburg, VA 24061 USA
[2] Catholic Univ Amer, Washington, DC 20064 USA
[3] Univ Memphis, Memphis, TN 38152 USA
来源：
INDEPENDENT COMPONENT ANALYSES, COMPRESSIVE SAMPLING, WAVELETS, NEURAL NET, BIOSYSTEMS, AND NANOENGINEERING XII | 2014年 / 9118卷
关键词：
software-defined camera; molecular thermodynamics; neuromorphic learning algorithm;
D O I：
10.1117/12.2052021
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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 non-trivial solutions, stability, and accuracy. An example neuromorphic learning algorithm is presented along with unsupervised learning stopping criteria.
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页数：10
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