会议论文详细信息
6th Annual 2018 International Conference on Geo-Spatial Knowledge and Intelligence | |
A Flower Auto-Recognition System Based on Deep Learning | |
Shi, Lin^1 ; Li, Zhigang^2 ; Song, Dingli^3 | |
Computer Science Department, North China University of Science and Technology, China^1 | |
Computer Center, TangShan College, China^2 | |
College of Science, North China University of Science and Technology, China^3 | |
关键词: CNN network; Daily lives; High-accuracy; Inter class; Intra-class variation; Recognition accuracy; Recognition systems; Transfer learning; | |
Others : https://iopscience.iop.org/article/10.1088/1755-1315/234/1/012088/pdf DOI : 10.1088/1755-1315/234/1/012088 |
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来源: IOP | |
【 摘 要 】
Building a flower auto recognition system with high accuracy is very significant. At the same time, it can bring convenience to our daily life. But Inter-class similarities between different species and the intra-class variation among the same species is a giant challenge needing addressed. Thus, this paper proposes a flower auto-recognition system based on deep learning, we get pictures by mobile smartphone and send the image to the CNN network, which is retrained by transfer learning based on Inception-V3. At last, an experiment was taken to verify the recognition accuracy is higher than other methods.
【 预 览 】
Files | Size | Format | View |
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A Flower Auto-Recognition System Based on Deep Learning | 510KB | download |