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jsbbs.21062.pdf | 10.24 MB | Adobe PDF | 見る/開く |
タイトル: | Automatic detection of alien plant species in action camera images using the chopped picture method and the potential of citizen science |
著者: | Takaya, Kosuke Sasaki, Yu Ise, Takeshi https://orcid.org/0000-0003-4331-5144 (unconfirmed) |
著者名の別形: | 高屋, 浩介 佐々木, 優 伊勢, 武史 |
キーワード: | deep learning chopped picture method alien plant Solidago altissima action camera citizen science computer vision |
発行日: | 2022 |
出版者: | Japanese Society of Breeding |
誌名: | Breeding Science |
巻: | 72 |
号: | 1 |
開始ページ: | 96 |
終了ページ: | 106 |
抄録: | Monitoring and detection of invasive alien plant species are necessary for effective management and control measures. Although efforts have been made to detect alien trees using satellite images, the detection of alien herbaceous species has been difficult. In this study, we examined the possibility of detecting non-native plants using deep learning on images captured by two action cameras. We created a model for each camera using the chopped picture method. The models were able to detect the alien plant Solidago altissima (tall goldenrod) and obtained an average accuracy of 89%. This study proved that it is possible to automatically detect exotic plants using inexpensive action cameras through deep learning. This advancement suggests that, in the future, citizen science may be useful for conducting distribution surveys of alien plants in a wide area at a low cost. |
著作権等: | © 2022 by JAPANESE SOCIETY OF BREEDING |
URI: | http://hdl.handle.net/2433/275806 |
DOI(出版社版): | 10.1270/jsbbs.21062 |
PubMed ID: | 36045894 |
出現コレクション: | 学術雑誌掲載論文等 |
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