A New Paphiopedilum Orchid Database and Its Recognition Using Convolutional Neural Network

被引：11

作者：

Arwatchananukul, Sujitra ^{[1
]}

Kirimasthong, Khwunta ^{[1
]}

Aunsri, Nattapol ^{[1
,2
]}

机构：

[1] Mae Fah Luang Univ, Sch Informat Technol, Chiang Rai, Thailand

[2] Mae Fah Luang Univ, Brain Sci & Engn Innovat Res Grp, Chiang Rai, Thailand

来源：

WIRELESS PERSONAL COMMUNICATIONS | 2020年 / 115卷 / 04期

关键词：

Paphiopedilum; Slipper orchid; Recognition; Convolutional neural networks (CNN); Deep learning; TensorFlow; Inception-v3;

D O I：

10.1007/s11277-020-07463-3

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

This paper discusses a visual recognition system, for identifying the Pa-phiopedilum orchid, often called the Venus slipper. The dataset consists of 100 sample images for each of 15 species of orchid, for a total of 1500 images. All the images of this dataset were taken at the Paphiopedilum orchid gardens and manually classified by experts. This work also implemented a recognition system based on a deep learning approach using a combination of convolutional neural network (CNN) and the Inception-v3 feature extractor of the TensorFlow platform. The implemented recognition system can deliver recognition rates of up to 98.6%, demonstrating excellent recognition performance by the CNN model. Finally, we demonstrate a prototype orchid recognition system, implemented as an Android mobile application.

引用

页码：3275 / 3289

页数：15

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