loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Manutur Siregar 1 ; Herman Mawengkang 2 and  Suyanto 2

Affiliations: 1 Master of Informatics Program, Faculty of Computer Science and Information Technology, Universitas Sumatra Utara, Medan, Indonesia ; 2 Department of Mathematics, Universitas Sumatra Utara, Medan, Indonesia

Keyword(s): CNN, Effect of Segmentation, Active Contour.

Abstract: Convolutional Neural Network is a type of deep learning that is used for image detection or image classification. The images used can be obtained from data banks such as http://www.kaggle.com, the image usually has a different image format, different width and height sizes also in some images contain noise. Segmentation is used to separate the image that becomes information from the noise contained therein. The types of segmentation used are active contour and K- Means and compared to not using segmentation at all. The Convolutional Neural Network architecture was also changed to obtain a better level of accuracy, and to take advantage of the existing CNN architectures such as Alexnet and GoogleNet. From the research conducted, the best accuracy results were obtained from the RGB Image model combined with the GoogleNet model, namely 98.37 K-Means segmentation has better test results when compared to the active contour for classifying lung disease.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 98.84.18.52

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Siregar, M.; Mawengkang, H. and Suyanto. (2024). The Effect of Segmentation and CNN Architecture in Determining Accuracy Convolutional Neural Network. In Proceedings of the 3rd International Conference on Advanced Information Scientific Development - ICAISD; ISBN 978-989-758-678-1, SciTePress, pages 46-51. DOI: 10.5220/0012441500003848

@conference{icaisd24,
author={Manutur Siregar. and Herman Mawengkang. and Suyanto.},
title={The Effect of Segmentation and CNN Architecture in Determining Accuracy Convolutional Neural Network},
booktitle={Proceedings of the 3rd International Conference on Advanced Information Scientific Development - ICAISD},
year={2024},
pages={46-51},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012441500003848},
isbn={978-989-758-678-1},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Information Scientific Development - ICAISD
TI - The Effect of Segmentation and CNN Architecture in Determining Accuracy Convolutional Neural Network
SN - 978-989-758-678-1
AU - Siregar, M.
AU - Mawengkang, H.
AU - Suyanto.
PY - 2024
SP - 46
EP - 51
DO - 10.5220/0012441500003848
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic