An Efficient Neural Network based on Early Compression of Sparse CT Slice Images
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Moon, A-Seong | - |
dc.contributor.author | Lee, Sanghyuck | - |
dc.contributor.author | Cho, Sung-Hyun | - |
dc.contributor.author | Lee, Tae-Won | - |
dc.contributor.author | Lee, Hanyong | - |
dc.contributor.author | Lee, Jaesung | - |
dc.date.accessioned | 2022-03-25T00:40:08Z | - |
dc.date.available | 2022-03-25T00:40:08Z | - |
dc.date.issued | 2021-08 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/55663 | - |
dc.description.abstract | Recently, research on diagnosing diseases through artificial intelligence has been conducted in various medical fields, including Thyroid-Associated ophthalmopathy. We introduce a computationally efficient CNN architecture, which is optimized for CT images and designed especially for mobile devices with very limited computing power. The proposed architecture utilizes three operations, pointwise convolution, depth-wise separable convolution and channel shuffle, to reduce computation cost for handling a series of CT image slices for a patient. On CT images, the proposed model achieves ∼ 3.5 × actual speedup over ShuffleNet-v2 without degenerating prediction accuracy. © 2021 IEEE. | - |
dc.format.extent | 5 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.title | An Efficient Neural Network based on Early Compression of Sparse CT Slice Images | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/PlatCon53246.2021.9680749 | - |
dc.identifier.bibliographicCitation | 2021 International Conference on Platform Technology and Service, PlatCon 2021 - Proceedings, pp 30 - 34 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000778774900006 | - |
dc.identifier.scopusid | 2-s2.0-85126236325 | - |
dc.citation.endPage | 34 | - |
dc.citation.startPage | 30 | - |
dc.citation.title | 2021 International Conference on Platform Technology and Service, PlatCon 2021 - Proceedings | - |
dc.type.docType | Proceedings Paper | - |
dc.subject.keywordAuthor | channel shuffle | - |
dc.subject.keywordAuthor | CT Image | - |
dc.subject.keywordAuthor | depthwise separable convolution | - |
dc.subject.keywordAuthor | efficiency | - |
dc.subject.keywordAuthor | lightweight deep learning | - |
dc.subject.keywordAuthor | pointwise convolution | - |
dc.subject.keywordAuthor | Thyroid-Associated ophthalmopathy | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
84, Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea (06974)02-820-6194
COPYRIGHT 2019 Chung-Ang University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.