Detection of Defects in Work-in-Process Products Using Deep Learning: A Case of a Water Tap Production Line-Reference-Cited by-同舟云学术

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Detection of Defects in Work-in-Process Products Using Deep Learning: A Case of a Water Tap Production Line

Published:2023-12-11 Issue: Volume: Page:369-372
ISSN:
Container-title:2023 6th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)
language:
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Author:

Piyasinchart Annop¹,Boonpoor Paradorn²,Thammachai Thantorn³,Daengsi Therdpong²

Affiliation:

1. SBU,Digital Business Technology,Bangkok,Thailand

2. RMUTP,Sustainable Industrial Management Engineering,Bangkok,Thailand

3. The Brainstem Co., Ltd.,Artificial Intelligence Solution,Bangkok,Thailand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10467179/10467216/10467717.pdf?arnumber=10467717

Reference20 articles.

1. Productivity Improvement Based on Measuring the Overall Equipment Effectiveness in Metal Formation Production Stages

2. Irrigation Management: A Pilot Study for Automatic Water Level Measurement and Report System Development U sing Machine Learning Associated with Modified Images;Daengsi;Proc. of ISRITI 2022, Yogyakarta, Indonesia,2022

3. Studies on application of image processing in various fields: An overview

4. An Overview on Nature-Inspired Optimization Algorithms and Their Possible Application in Image Processing Domain

5. Transfer learning for time series classification

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