Two-step transfer learning for semantic plant segmentation

Shunsuke Sakurai, Hideaki Uchiyama, Atsushi Shimada, Daisaku Arita, Rin ichiro Taniguchi

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

6 引用 (Scopus)

抜粋

We discuss the applicability of a fully convolutional network (FCN), which provides promising performance in semantic segmentation tasks, to plant segmentation tasks. The challenge lies in training the network with a small dataset because there are not many samples in plant image datasets, as compared to object image datasets such as ImageNet and PASCAL VOC datasets. The proposed method is inspired by transfer learning, but involves a two-step adaptation. In the first step, we apply transfer learning from a source domain that contains many objects with a large amount of labeled data to a major category in the plant domain. Then, in the second step, category adaptation is performed from the major category to a minor category with a few samples within the plant domain. With leaf segmentation challenge (LSC) dataset, the experimental results confirm the effectiveness of the proposed method such that F-measure criterion was, for instance, 0.953 for the A2 dataset, which was 0.355 higher than that of direct adaptation, and 0.527 higher than that of non-adaptation.

元の言語英語
ホスト出版物のタイトルICPRAM 2018 - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods
編集者Maria De Marsico, Gabriella Sanniti di Baja, Ana Fred
出版者SciTePress
ページ332-339
ページ数8
ISBN(電子版)9789897582769
DOI
出版物ステータス出版済み - 2018
イベント7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018 - Funchal, Madeira, ポルトガル
継続期間: 1 16 20181 18 2018

出版物シリーズ

名前ICPRAM 2018 - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods
2018-January

その他

その他7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018
ポルトガル
Funchal, Madeira
期間1/16/181/18/18

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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  • これを引用

    Sakurai, S., Uchiyama, H., Shimada, A., Arita, D., & Taniguchi, R. I. (2018). Two-step transfer learning for semantic plant segmentation. : M. De Marsico, G. S. di Baja, & A. Fred (版), ICPRAM 2018 - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods (pp. 332-339). (ICPRAM 2018 - Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods; 巻数 2018-January). SciTePress. https://doi.org/10.5220/0006576303320339