産業応用工学会論文誌
Online ISSN : 2187-5146
Print ISSN : 2189-373X
ISSN-L : 2187-5146
論文
Data Augmentationを用いたCNN学習画像の増加による害鳥認識システムの認識率の改善
北風 裕教岡部 蒼太吉原 蓮人松村 遼
著者情報
ジャーナル オープンアクセス

2019 年 7 巻 2 号 p. 69-76

詳細
抄録
In this paper, we discuss injurious bird recognition system that we have developed. Among injurious bird, the damage of Plecoglossus altivelis and Oncorhynchus masou by Phalacrocorax carbo are especially large. In recent years, some researchers have been trying to automatically identify this injurious bird using a surveillance system. However, it was difficult to identify the Phalacrocorax carbo from images including background and other wild birds. Therefore, our research grope examined a method of identification using a convolutional neural network. In order to improve recognition accuracy, learning images were increased by realizing data augmentation of 3 stages. As a result of investigating about this effect, it was able to improve to about 80% of recognition rate.
著者関連情報

この記事は最新の被引用情報を取得できません。

© 2019 一般社団法人 産業応用工学会
前の記事 次の記事
feedback
Top