High-efficient Semantic Segmentation for Internet-of-Things-enabled Smart Cameras

Kuan Ting Lai; Jirayu Petchhan; Ching Hu Lu

doi:10.1109/ICCE-TW52618.2021.9603215

High-efficient Semantic Segmentation for Internet-of-Things-enabled Smart Cameras

Kuan Ting Lai
, Jirayu Petchhan
, Ching Hu Lu

電子工程系

研究成果: 書籍/報告/會議論文中的章節 › 會議投稿 › 同行評審

1 引文斯高帕斯（Scopus）

摘要

Even in the era of the Internet of Things (IoT), existing smart cameras still cannot efficiently run complex neural networks of image segmentation due to restricted storage and computing capacities. To address this issue, we proposed a high-efficient semantic segmentation for IoT-enabled smart cameras. The experiment results show that the accuracy of the proposed semantic segmentation model can improve the classwise accuracy by 4%, given that the model is reduced by 12.5% and even runs faster than prior studies.

原文	English
主出版物標題	2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
發行者	Institute of Electrical and Electronics Engineers Inc.
ISBN（電子）	9781665433280
DOIs	https://doi.org/10.1109/ICCE-TW52618.2021.9603215
出版狀態	Published - 2021
事件	8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021 - Penghu, Taiwan 持續時間: 15 9月 2021 → 17 9月 2021

出版系列

名字	2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

Conference

Conference	8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
國家/地區	Taiwan
城市	Penghu
期間	15/09/21 → 17/09/21

文獻附註

Publisher Copyright:
© 2021 IEEE.

存取文件

10.1109/ICCE-TW52618.2021.9603215

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Link to publication in Scopus

引用此

Lai, K. T., Petchhan, J., & Lu, C. H. (2021). High-efficient Semantic Segmentation for Internet-of-Things-enabled Smart Cameras. 於 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021 (2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE-TW52618.2021.9603215

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title = "High-efficient Semantic Segmentation for Internet-of-Things-enabled Smart Cameras",

abstract = "Even in the era of the Internet of Things (IoT), existing smart cameras still cannot efficiently run complex neural networks of image segmentation due to restricted storage and computing capacities. To address this issue, we proposed a high-efficient semantic segmentation for IoT-enabled smart cameras. The experiment results show that the accuracy of the proposed semantic segmentation model can improve the classwise accuracy by 4\%, given that the model is reduced by 12.5\% and even runs faster than prior studies.",

author = "Lai, \{Kuan Ting\} and Jirayu Petchhan and Lu, \{Ching Hu\}",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021 ; Conference date: 15-09-2021 Through 17-09-2021",

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Lai, KT, Petchhan, J & Lu, CH 2021, High-efficient Semantic Segmentation for Internet-of-Things-enabled Smart Cameras. 於 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021. 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021, Institute of Electrical and Electronics Engineers Inc., 8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021, Penghu, Taiwan, 15/09/21. https://doi.org/10.1109/ICCE-TW52618.2021.9603215

High-efficient Semantic Segmentation for Internet-of-Things-enabled Smart Cameras. / Lai, Kuan Ting; Petchhan, Jirayu; Lu, Ching Hu.
2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021. Institute of Electrical and Electronics Engineers Inc., 2021. (2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021).

研究成果: 書籍/報告/會議論文中的章節 › 會議投稿 › 同行評審

TY - GEN

T1 - High-efficient Semantic Segmentation for Internet-of-Things-enabled Smart Cameras

AU - Lai, Kuan Ting

AU - Petchhan, Jirayu

AU - Lu, Ching Hu

PY - 2021

Y1 - 2021

N2 - Even in the era of the Internet of Things (IoT), existing smart cameras still cannot efficiently run complex neural networks of image segmentation due to restricted storage and computing capacities. To address this issue, we proposed a high-efficient semantic segmentation for IoT-enabled smart cameras. The experiment results show that the accuracy of the proposed semantic segmentation model can improve the classwise accuracy by 4%, given that the model is reduced by 12.5% and even runs faster than prior studies.

AB - Even in the era of the Internet of Things (IoT), existing smart cameras still cannot efficiently run complex neural networks of image segmentation due to restricted storage and computing capacities. To address this issue, we proposed a high-efficient semantic segmentation for IoT-enabled smart cameras. The experiment results show that the accuracy of the proposed semantic segmentation model can improve the classwise accuracy by 4%, given that the model is reduced by 12.5% and even runs faster than prior studies.

UR - https://www.scopus.com/pages/publications/85123056442

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T3 - 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

BT - 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

Y2 - 15 September 2021 through 17 September 2021

ER -

Lai KT, Petchhan J, Lu CH. High-efficient Semantic Segmentation for Internet-of-Things-enabled Smart Cameras. 於 2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021. Institute of Electrical and Electronics Engineers Inc. 2021. (2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021). doi: 10.1109/ICCE-TW52618.2021.9603215

High-efficient Semantic Segmentation for Internet-of-Things-enabled Smart Cameras

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