Random Forest Based Adaptive DBSCAN for Reducing Noise in mmWave Radar Point Clouds-Reference-Cited by-同舟云学术

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Random Forest Based Adaptive DBSCAN for Reducing Noise in mmWave Radar Point Clouds

Published:2022-12-08 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 21st International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)
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Author:

Zhou Houpu¹,Zhang Guochen¹,Kong Lin¹,Huang Runhe¹

Affiliation:

1. Hosei University,Computer and Information Sciences,Tokyo,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10101484/10100740/10101513.pdf?arnumber=10101513

Reference18 articles.

1. A density-based algorithm for discovering clusters in large spatial databases with noise;ester;KDD,1996

2. Testing non-wearable fall detection methods in the homes of older adults

3. mID: Tracking and Identifying People with Millimeter Wave Radar

4. KNN-DBSCAN: Using k-nearest neighbor information for parameter-free density based clustering

5. On the Correlation of Sensor Location and Human Activity Recognition in Body Area Networks (BANs)

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