Ultra-wideband Impulse Radar Classification of Materials using a Convolutional Neural Network-Reference-Cited by-同舟云学术

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Ultra-wideband Impulse Radar Classification of Materials using a Convolutional Neural Network

Published:2023-10-19 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Advanced Technologies for Communications (ATC)
language:
Short-container-title:

Author:

Le Minhhuy¹,Mach Tuan Kiet Tran²,Luong Van Su¹,Van Khai Nguyen²,Vu Hong Ha Thi³

Affiliation:

1. Phenikaa University,Faculty of Electrical and Electronic Engineering,Hanoi,Vietnam,12116

2. Phenikaa University,Intelligent Communication System Laboratory (ICSLab),Hanoi,Vietnam,12116

3. Phenikaa University,Faculty of Biotechnology, Chemistry, and Environmental Engineering,Hanoi,Vietnam,12116

Funder

Foundation for Science and Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10318513/10318514/10318919.pdf?arnumber=10318919

Reference18 articles.

1. Robust material classification with a tactile skin using deep learning

2. A multimodal approach to continuous material identification through tactile sensing;eguluz;IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),2016

3. Statistical Approaches to Material Classification;varma;ICVGIP,2002

4. A short survey on optical material recognition;weinmann;Proceedings of the Third Workshop on Material Appearance Modeling Issues and Acquisition (MAM ’15),2015

5. Time-Domain Measurements for Determination of Dielectric Properties of Agricultural Materials

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