A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-Time Systems-Reference-Cited by-同舟云学术

A Hybrid Neuromorphic Object Tracking and Classification Framework for Real-Time Systems

Published:2023 Issue: Volume: Page:1-10
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Ussa Andres¹^ORCID,Rajen Chockalingam Senthil¹^ORCID,Pulluri Tarun¹,Singla Deepak²,Acharya Jyotibdha²^ORCID,Chuanrong Gideon Fu¹,Basu Arindam³^ORCID,Ramesh Bharath¹^ORCID

Affiliation:

1. N.1 Institute for Health, National University of Singapore, Singapore, Singapore

2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

3. Department of Electrical Engineering, City University of Hong Kong, Hong Kong, Hong Kong

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10047993.pdf?arnumber=10047993

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