@inproceedings{c9869bb4ab2e45968a9b555c2d41cb48,
title = "Defect Detection on Wafer Map Using Efficient Convolutional Neural Network",
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%. ",
author = "Wang, {Chieng Yang} and Tsai, {Tsung Han}",
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",
year = "2021",
doi = "10.1109/ICCE-TW52618.2021.9603145",
language = "???core.languages.en_GB???",
series = "2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 IEEE International Conference on Consumer Electronics-Taiwan, ICCE-TW 2021",
}