Paper
12 October 2022 Rapid identification of mature Xanthoceras sorbifolium bunge
Xia Geng, Yufei Zhang, Baoxin Wu, Wenwen Zhu, Han Li
Author Affiliations +
Proceedings Volume 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022); 123423C (2022) https://doi.org/10.1117/12.2644452
Event: Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 2022, Wuhan, China
Abstract
Xanthoceras sorbifolium bunge is a kind of edible oil tree in China, which has very high economic value, but the timely picking of mature fruits is a problem that has troubled farmers for a long time. To rapidly, automatically and accurately identify mature Xanthoceras sorbifolium bunge in the field, a mobile data acquisition and transmission system was firstly designed based on the architecture of the Internet of Things, which provides image acquisition and positioning tools for timely and accurate picking of Xanthoceras sorbifolium bunge. Secondly, a mature Xanthoceras sorbifolium bunge identification network model was constructed based on the lightweight efficient model YOLOv3 by using convolutional neural network (CNN) and flip residual network. The established optimal identification model was evaluated, the results of which indicate that the constructed optimal model can serve as a tool to identify the maturity of Xanthoceras sorbifolium bunge with the mAP of 97.04%.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xia Geng, Yufei Zhang, Baoxin Wu, Wenwen Zhu, and Han Li "Rapid identification of mature Xanthoceras sorbifolium bunge", Proc. SPIE 12342, Fourteenth International Conference on Digital Image Processing (ICDIP 2022), 123423C (12 October 2022); https://doi.org/10.1117/12.2644452
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KEYWORDS
Data modeling

Image acquisition

Control systems

Data acquisition

Data storage

Performance modeling

Computing systems

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