Fingerprint-based Indoor Localization using Weighted K-Nearest Neighbor and Weighted Signal Intensity-Reference-Cited by-同舟云学术

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Fingerprint-based Indoor Localization using Weighted K-Nearest Neighbor and Weighted Signal Intensity

Published:2020-10-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture
language:
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Author:

Zhang Liwei¹,Zhao Changming²,Wang Yunshi²,Dai Lei³

Affiliation:

1. School of Optics and Photonics, Beijing Institute of Technology, CETC China Academy of Electronics and Information Technology, Beijing, China

2. School of Optics and Photonics, Beijing Institute of Technology, Beijing, China

3. CETC China Academy of Electronics and Information Technology, Beijing, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3421766.3421813

Reference12 articles.

1. Indoor location based services challenges, requirements and usability of current solutions

2. Smartphone Location Recognition: A Deep Learning-Based Approach

3. An Outdoor Navigation System for Blind Pedestrians Using GPS and Tactile-Foot Feedback

4. Object Detection-Based Location and Activity Classification from Egocentric Videos: A Systematic Analysis

5. Estimation of Indoor Location Through Magnetic Field Data: An Approach Based On Convolutional Neural Networks

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. Google Trends to Investigate the Degree of Global Interest Related to Indoor Location Detection;Human Interaction, Emerging Technologies and Future Systems V;2021-09-10

2. Multimodal Approaches for Indoor Localization for Ambient Assisted Living in Smart Homes;Information;2021-03-07

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