Fast Detection of Objects Using a YOLOv3 Network for a Vending Machine

Youhak Lee; Chulhee Lee; Hyuk Jae Lee; Jin Sung Kim

doi:10.1109/AICAS.2019.8771517

Fast Detection of Objects Using a YOLOv3 Network for a Vending Machine

Youhak Lee, Chulhee Lee, Hyuk Jae Lee, Jin Sung Kim

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Citations (Scopus)

Abstract

Fast object detection is important to enable a vision-based automated vending machine. This paper proposes a new scheme to enhance the operation speed of YOLOv3 by removing the computation for the region of non-interest. In order to avoid the accuracy drop by a removal of computation, characteristics of a convolutional layer and a YOLO layer are investigated, and a new processing method is proposed from experimental results. As a result, the operation speed is increased in proportion to the size of the region of non-interest. Experimental results show that the speed is improved by 3.29 times while the accuracy degradation is 2.81% in mAP-50.

Original language	English
Title of host publication	Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	132-136
Number of pages	5
ISBN (Electronic)	9781538678848
DOIs	https://doi.org/10.1109/AICAS.2019.8771517
Publication status	Published - 2019 Mar
Event	1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019 - Hsinchu, Taiwan, Province of China Duration: 2019 Mar 18 → 2019 Mar 20

Publication series

Name	Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019

Conference

Conference	1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019
Country/Territory	Taiwan, Province of China
City	Hsinchu
Period	19/3/18 → 19/3/20

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Hardware and Architecture
Electrical and Electronic Engineering

Access to Document

10.1109/AICAS.2019.8771517

Cite this

Lee, Y., Lee, C., Lee, H. J., & Kim, J. S. (2019). Fast Detection of Objects Using a YOLOv3 Network for a Vending Machine. In Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019 (pp. 132-136). [8771517] (Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AICAS.2019.8771517

Lee, Youhak ; Lee, Chulhee ; Lee, Hyuk Jae ; Kim, Jin Sung. / Fast Detection of Objects Using a YOLOv3 Network for a Vending Machine. Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 132-136 (Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019).

@inproceedings{27ae3926d4ac400087df003e5b576c94,

title = "Fast Detection of Objects Using a YOLOv3 Network for a Vending Machine",

abstract = "Fast object detection is important to enable a vision-based automated vending machine. This paper proposes a new scheme to enhance the operation speed of YOLOv3 by removing the computation for the region of non-interest. In order to avoid the accuracy drop by a removal of computation, characteristics of a convolutional layer and a YOLO layer are investigated, and a new processing method is proposed from experimental results. As a result, the operation speed is increased in proportion to the size of the region of non-interest. Experimental results show that the speed is improved by 3.29 times while the accuracy degradation is 2.81% in mAP-50.",

author = "Youhak Lee and Chulhee Lee and Lee, {Hyuk Jae} and Kim, {Jin Sung}",

year = "2019",

month = mar,

doi = "10.1109/AICAS.2019.8771517",

language = "English",

series = "Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "132--136",

booktitle = "Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019",

address = "United States",

note = "1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019 ; Conference date: 18-03-2019 Through 20-03-2019",

}

Lee, Y, Lee, C, Lee, HJ & Kim, JS 2019, Fast Detection of Objects Using a YOLOv3 Network for a Vending Machine. in Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019., 8771517, Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019, Institute of Electrical and Electronics Engineers Inc., pp. 132-136, 1st IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019, Hsinchu, Taiwan, Province of China, 19/3/18. https://doi.org/10.1109/AICAS.2019.8771517

Fast Detection of Objects Using a YOLOv3 Network for a Vending Machine. / Lee, Youhak; Lee, Chulhee; Lee, Hyuk Jae; Kim, Jin Sung.

Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 132-136 8771517 (Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Fast Detection of Objects Using a YOLOv3 Network for a Vending Machine

AU - Lee, Youhak

AU - Lee, Chulhee

AU - Lee, Hyuk Jae

AU - Kim, Jin Sung

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N2 - Fast object detection is important to enable a vision-based automated vending machine. This paper proposes a new scheme to enhance the operation speed of YOLOv3 by removing the computation for the region of non-interest. In order to avoid the accuracy drop by a removal of computation, characteristics of a convolutional layer and a YOLO layer are investigated, and a new processing method is proposed from experimental results. As a result, the operation speed is increased in proportion to the size of the region of non-interest. Experimental results show that the speed is improved by 3.29 times while the accuracy degradation is 2.81% in mAP-50.

AB - Fast object detection is important to enable a vision-based automated vending machine. This paper proposes a new scheme to enhance the operation speed of YOLOv3 by removing the computation for the region of non-interest. In order to avoid the accuracy drop by a removal of computation, characteristics of a convolutional layer and a YOLO layer are investigated, and a new processing method is proposed from experimental results. As a result, the operation speed is increased in proportion to the size of the region of non-interest. Experimental results show that the speed is improved by 3.29 times while the accuracy degradation is 2.81% in mAP-50.

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M3 - Conference contribution

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BT - Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019

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Lee Y, Lee C, Lee HJ, Kim JS. Fast Detection of Objects Using a YOLOv3 Network for a Vending Machine. In Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 132-136. 8771517. (Proceedings 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2019). https://doi.org/10.1109/AICAS.2019.8771517

Fast Detection of Objects Using a YOLOv3 Network for a Vending Machine

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