LEAF + AIO: Edge-Assisted Energy-Aware Object Detection for Mobile Augmented Reality

Author:

Wang Haoxin1,Kim BaekGyu2,Xie Jiang Linda3,Han Zhu4

Affiliation:

1. N/A, Toyota Motor North America, InfoTech Labs, Mountain View, California, United States

2. Department of Information and Communication Engineering (ICE), DGIST, 235496 Daegu, NA, Korea (the Republic of)

3. Department of Electrical and Computer Engineering, The University of North Carolina at Charlotte, Charlotte, North Carolina, United States, 28223-0001

4. Electrical and Computer Engineering, University of Houston, Houston, Texas, United States, 77004

Funder

U.S. National Science Foundation

Toyota Motor North America

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Software

Cited by 9 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. HarvAR: Mobile Augmented-Reality-Assisted Photovoltaic Energy-Harvesting Sensor Management;IEEE Internet of Things Journal;2024-09-01

2. ExposureNet: Mobile camera exposure parameters autonomous control for blur effect prevention;IET Image Processing;2024-07-25

3. A Performance Analysis Modeling Framework for Extended Reality Applications in Edge-Assisted Wireless Networks;2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS);2024-07-23

4. Analysis of H.266 Versatile Video Coding Streaming and Decoding for XR & HDR on Smartphones;2024 IEEE International Conference on Consumer Electronics (ICCE);2024-01-06

5. Unveiling Energy Efficiency in Deep Learning: Measurement, Prediction, and Scoring across Edge Devices;Proceedings of the Eighth ACM/IEEE Symposium on Edge Computing;2023-12-06

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