@inproceedings{df0e48e3008b43d08ecf90e2b653d8a4,
title = "Rice Semantic Segmentation Using Unet-VGG16: A Case Study in Yunlin, Taiwan",
abstract = "In this paper, Unet-VGG16 semantic segmentation network is proposed to segment rice regions in the aerial images of Yunlin, Taiwan. The experimental results show that different combinations of image bands and different image conditions affect the segmentation accuracy. With R-G-NIR bands as input and bright aerial images as the dataset, the Unet-VGG16 network yielded the best segmentation result, achieving a test accuracy of 0.91.",
keywords = "Deep Learning, Rice, Semantic Segmentation, Taiwan, Unet-VGG16",
author = "Ida Wahyuni and Wang, {Wei Jen} and Deron Liang and Chang, {Chin Chun}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2021 ; Conference date: 16-11-2021 Through 19-11-2021",
year = "2021",
doi = "10.1109/ISPACS51563.2021.9651038",
language = "???core.languages.en_GB???",
series = "ISPACS 2021 - International Symposium on Intelligent Signal Processing and Communication Systems: 5G Dream to Reality, Proceeding",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ISPACS 2021 - International Symposium on Intelligent Signal Processing and Communication Systems",
}