Feature Sequence Fusion Faster R-CNN-Based Metal Foreign Object Detection for Electric Vehicle Wireless Power Transfer System-Reference-Cited by-同舟云学术

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Feature Sequence Fusion Faster R-CNN-Based Metal Foreign Object Detection for Electric Vehicle Wireless Power Transfer System

Published:2023-12-15 Issue: Volume:28 Page:3713-3719
ISSN:
Container-title:2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2)
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Author:

Wu Thomas¹,Yang Xueqing²,Zhu Hongyu²,Wu Yingxin³,Yang Lina⁴,Zhang Dongdong¹

Affiliation:

1. School of Electrical Engineering, Guangxi University, School of Computer, Electronics and Information, Guangxi University,Nanning,China

2. School of Electrical Engineering, Guangxi University,Nanning,China

3. Jinan University,Energy and Electric Power Research Center,Guangzhou,China

4. School of Computer, Electronics and Information, Guangxi University,Nanning,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10511272/10512350/10512647.pdf?arnumber=10512647

Reference23 articles.

1. Key technologies for smart energy systems: Recent developments, challenges, and research opportunities in the context of carbon neutrality

2. Dynamic resource allocation for parking lot electric vehicle recharging using heuristic fuzzy particle swarm optimization algorithm

3. Reservation-based EV charging recommendation concerning charging urgency policy

4. Object Detection With Deep Learning: A Review

5. Multi objective Optimization for Smart Integrated Energy System Considering Demand Responses and Dynamic Prices

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