Defect Detection on Wafer Map Using Efficient Convolutional Neural Network

Chieng Yang Wang, Tsung Han Tsai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In semiconductor manufacturing, defect patterns on wafer maps hide important information about production problems. Therefore, the detection and identification of wafer pattern defects are one of the important topics in semiconductor manufacturing. Since there are few datasets of wafer maps, this paper solves the problem of overfitting by classifying wafer map defects using the model base on MobileNet V2. Finally, the accuracy of the WM-811K dataset reaches 96.56%.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665433280
DOIs
StatePublished - 2021
Event8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021 - Penghu, Taiwan
Duration: 15 Sep 202117 Sep 2021

Publication series

Name2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021

Conference

Conference8th IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021
Country/TerritoryTaiwan
CityPenghu
Period15/09/2117/09/21

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