Evaluation and discussion of classification accuracy for texture of PSPNet

PSPNet の質感に対するクラス分類精度の評価と考察

Evaluation and discussion of classification accuracy for texture of PSPNet

Creators Okamura Kazuya

Creators Matsumura Ryo

Creators Kitakaze Hironori

In recent years, damage to fisheries caused by Phalacrocorax carbo occurs throughout Japan. Our research group have been developing system for driving away verminous birds by using drone. In previous research, a method that PSPNet and original classifier is proposed. But there are problems such as the inability to cope with an increase in number of target objects. Therefore, in this paper, confirmation that whether PSPNet can classify with high accuracy and discuss classification accuracy for texture. As a result, it could be confirmed that classifying with high accuracy in 4 classes airplane, car, crow, and boar.

[PISSN]0387-9232

[NCID]AN00031668