KIC Program

About IPL

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Team

  • IPL(Image Processing LAB)
    • JinSeon Oh(오진선)
    • GeumJu Ko (고금주)
    • DongWoo Lee(이동우)
    • JeongYoon Joo(주정윤)

JinSeon Oh


  • Name : JinSeon Oh
  • Incharge : Image Processing LAB, Bachelor of dept.Computer Science Engineering @ Univ.SoonCheonHyang

Current Interest

  • Artifitial Intelligence
  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Data Analysis

Career & Activities

Let me say one thing…

Thank you for your high regard for our insufficient project. I would like to urge myself to continue growing.

Contact

GeumJu Ko


  • Name : GeumJu Ko
  • Incharge : Image Processing LAB, Bachelor of dept.Computer Science Engineering @ Univ.SoonCheonHyang

Current Interest

  • Artifitial Intelligence
  • Computer Vision
  • Data Science

Career & Activities

Let me say one thing…

I am happy to have a good experience participating in Kpmg ideathon 2020. I will continue to show you my growth.

Contact

DongWoo Lee


  • Name : DongWoo Lee
  • Incharge : Image Processing LAB, Bacheler of dept. Computer Science Engineering @ Univ.SoonCheonHyang

Current Interest

  • Application
  • Internet of Things
  • Sensor of Hardware

Career & Activities

  • 2015.03 ~ attending in SCH
  • 2019.04 ~ Member of IPL Lab in SCH

Let me say one thing

Through this good opportunity, I will show my progress and become a person who is not lazy and tries hard.

Contact

JeongYoon Joo


  • Name : JeongYoon Joo
  • Incharge : Image Processing LAB, Bachelor of dept.Computer Science Engineering @ Univ.SoonCheonHyang

Current Interest

  • Front-End & Back-End
  • Machine Learning
  • Unity Dev

Career & Activities

Let me say one thing

I will always be a developing developer.

Contact

Product



Recently, many attempts have been made to reduce the time required for payment in various shopping environments.
In addition, as the 4th Industrial Revolution era, artificial Intelligence technology is advancing and IoT devices are becoming more compact and cheaper.
So, by integrating these two thechnologies, access to building an unmanned environment on behalf of human beings to save users’ time became easier.
In this paper, we propose a smart shopping cart system based on low-cost IoT equipment and deep learning object detection technology.
The proposed smart cart system consists of a camera for real-time product detection, an ultrasonic sensor that acts as a trigger, a weight sensor to determine whether a product enters into or out of shopping cart, and an application of smartphone that provides a UI for a virtual shopping cart, and a deep learning server where learned product data are stored.
Commuication between each module is made of TCP/IP and HTTP network, and YOLO darknet library, an object detection system is used by the server to recognize the product.
The user can check the list of items put in the smart cart through the app of the smartphone and automatically pay.
The smart cart system proposed in this paper can be applied to implement unmanned stores with high cost-performance ratio.


PR

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‘KPMG Ideathon’ 개최 사후 보도결과

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Munhwa(문화일보)

YNA(연합뉴스)

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