Evaluation and discussion of classification accuracy for texture of PSPNet
大島商船高等専門学校紀要 Volume 55
Page 6-12
published_at 2022-12
Title
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
Source Identifiers
[PISSN] 0387-9232
[NCID] AN00031668
Creator Keywords
Deep Learning
Pyramid Scene Parsing Network
Semantic Segmentation
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.
Resource Type
departmental bulletin paper
Publishers
National Institute of Technology,Oshima College
Date Issued
2022-12
File Version
Version of Record
Access Rights
open access
Relations
[PISSN]0387-9232
[NCID]AN00031668