An efficient No-Line-of-Sight learning approach for Prediction of Static Victim Detection Using Genetic Algorithm and Kth Nearest Neighbor Data Classification-Reference-Cited by-同舟云学术

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An efficient No-Line-of-Sight learning approach for Prediction of Static Victim Detection Using Genetic Algorithm and Kth Nearest Neighbor Data Classification

Published:2024-04-02 Issue: Volume:17 Page:1-6
ISSN:
Container-title:2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG)
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Author:

Enoch Jiya Adana¹,Oluwafemi Ilesanmi B.²,Ibikunle Francis A.¹,Paul Olulope K.²,Yusuf Isaac Onimisi¹,Michael Arowolo O.³

Affiliation:

1. Landmark Universuty Omu-Aran,Department of Electrical and Information Engineering,Omu-Aran,Nigeria

2. Ekiti State Universuty Ado Ekiti,Department of Electrical and Elctronic Engineering,Ado Ekiti,Nigeria

3. University of Missouri,Department of Electrical Engineering and Computer Science,Columbia,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10629651/10629654/10630421.pdf?arnumber=10630421

Reference38 articles.

1. Survey of Sensors and Techniques in Microwave Imaging for Through-Wall Imaging for Detecting Trapped Humans under Rubble;Jiya

2. Disasters Offspring: Catastrophe, Narrative and Society;Rodrigue,2023

3. SPOTTER: Detection of Human Beings Under Collapsed Environment;Aparna,2020

4. An Analysis on the Performance of a Mobile Platform with Gas Sensors for Real Time Victim Localization

5. A Comparative Performance Study of Support Vector Machine, KNN, and Ensemble Classifiers on through-wall human detection Dataset;Jiya

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