VIP-STB Farm: Scale-up Village to County/Province Level to Support Science and Technology at Backyard (STB) Program
文献类型： 外文期刊
第一作者： Yan, Yijun
作者： Yan, Yijun;Zhao, Sophia;Fang, Yuxi;Liu, Yuren;Ren, Jinchang;Chen, Zhongxin
作者机构：
关键词： Precision agriculture; Machine learning; Information fusion
期刊名称：ADVANCES IN BRAIN INSPIRED COGNITIVE SYSTEMS （ 影响因子：0.302； ）
ISSN： 0302-9743
年卷期： 2020 年 11691 卷
页码：
收录情况： SCI
摘要： In this paper, we introduce a new concept in VIP-STB, a funded project through Agri-Tech in China: Newton Network+ (ATCNN), in developing feasible solutions towards scaling-up STB from village level to upper level via some generic models and systems. There are three tasks in this project, i.e. normalized difference vegetation index (NDVI) estimation, wheat density estimation and household-based small farms (HBSF) engagement. In the first task, several machine learning models have been used to evaluate the performance of NDVI estimation. In the second task, integrated software via Python and Twilio is developed to improve communication services and engagement for HBSFs, and provides technical capabilities. In the third task, crop density/ population is predicted by conventional image processing techniques. The objectives and strategy for VIP-STB are described, experimental results on each task are presented, and more details on each model that has been implemented are also provided with future development guidance.
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