NeuroSEE: A Neuromorphic Energy-Efficient Processing Framework for Visual Prostheses
Author:
Affiliation:
1. School of Information Science and Technology, Fudan University, Shanghai, China
2. CenBRAIN, School of Engineering, Westlake University, Hangzhou, Zhejiang, China
Funder
Zhejiang Key R&D Program
Zhejiang Leading Innovative and Entrepreneur Team Introduction Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics
Link
http://xplorestaging.ieee.org/ielx7/6221020/9855434/09767670.pdf?arnumber=9767670
Reference40 articles.
1. An Embedded Real-Time Processing Platform for Optogenetic Neuroprosthetic Applications
2. High Density, High Radiance $\mu$ LED Matrix for Optogenetic Retinal Prostheses and Planar Neural Stimulation
3. Revealing structure components of the retina by deep learning networks;yan;Proc NIPS Symp Interpretable Mach Learn,0
4. High-performance CMOS image sensor power supply in industrial camera and vision;wu;Appl Rep Tex Instrum,2019
5. 1.1 computing’s energy problem (and what we can do about it;horowitz;Proc IEEE Int Solid-State Circuits Conf Dig Tech Papers,0
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Improved VGG Algorithm for Visual Prosthesis Image Recognition;IEEE Access;2024
2. Artificial intelligence techniques for retinal prostheses: a comprehensive review and future direction;Journal of Neural Engineering;2023-02-01
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