Discrete Tomography Approach for Subsurface Object Detection by Artificial Neural Network-Reference-Cited by-同舟云学术

Discrete Tomography Approach for Subsurface Object Detection by Artificial Neural Network

Published:2022-11-14 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 2nd Ukrainian Microwave Week (UkrMW)
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Author:

Pryshchenko Oleksandr¹,Dumin Oleksandr¹,Plakhtii Vadym¹

Affiliation:

1. School of Radio Physics, Biomedical Electronics and Computer Systems, V. N. Karazin Kharkiv National University,Kharkiv,Ukraine

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10036686/10036948/10037072.pdf?arnumber=10037072

Reference36 articles.

1. Landmine detection and classification using UWB antenna system and ANN analysis

2. Recognition of microwave multifrequency images of objects hidden behind wall

3. Measurement of displacement parameters for plane elements by the microwave method using neural network tecknologies

4. Recognition multifrequency microwave images of simple objects behind dielectric wall using neural networks and correlation technique;Drobakhin,2013

5. Non-metallic pipe detection using SF-GPR: A new approach using neural network

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1. Noise-Resistant Remote Sensing System Based on Discrete Tomography Approach and Artificial Intelligence;2023 IEEE International Conference on Information and Telecommunication Technologies and Radio Electronics (UkrMiCo);2023-11-13

2. Discrete Tomography Approach for Subsurface Object Detection by Artificial Neural Network;2023 XXXVth General Assembly and Scientific Symposium of the International Union of Radio Science (URSI GASS);2023-08-19