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A Prototype Model for Semantic Segmentation of Curvilinear Meandering Regions by Deconvolutional Neural Networks Cover

A Prototype Model for Semantic Segmentation of Curvilinear Meandering Regions by Deconvolutional Neural Networks

Applied Computer Systems
Volume 25 (2020): Issue 1 (May 2020)
By:   
Open Access
|Jun 2020
Authors

Authors

Vadim Romanuke

romanukevadimv@gmail.com

Polish Naval Academy, Gdynia, Poland
DOI: https://doi.org/10.2478/acss-2020-0008 | Journal eISSN: 2255-8691 | Journal ISSN: 2255-8683
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Language: English
Page range: 62 - 69
Published on: Jun 5, 2020
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
Curvilinear meandering region,
deconvolutional layer,
empty image segmentation,
mean BF score,
neural network,
overfitting,
semantic segmentation,
toy dataset
Related subjects:
Computer sciences,
Artificial intelligence,
Information technology,
Project management,
Software development

© 2020 Vadim Romanuke, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 25 (2020): Issue 1 (May 2020)
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