摘要
The deployment of intelligent surveillance systems to monitor tomato plant growth poses substantial challenges due to the dynamic nature of disease patterns and the complexity of environmental conditions such as background and lighting.In this study,an integrated cascade framework that synergizes detectors and trackers was introduced for the simultaneous identification of tomato leaf diseases and fruit counting.We applied an autonomous robot with smartphone camera to collect images for leaf disease and fruits in greenhouses.
基金
partially supported by the Nation al Key Research and Development Program of China(2022YFD2100601)
the Key Research and Development Program of Jiangsu Province(BE2021379)
the Agricultural Independent Innovation of Jiangsu Province(CX225009)
the National Natural Science Foundation of China(32102081)
Fonds de Recherche du Québec Nature et technologies(FRQNT)Programme de recherche en partenariat—Agriculture durable(grant no.G259806 FRQ-NT 322853 X-Coded 259432)
R.K.extends his appreciation for the scholarship provided by CSC
the fund from 333 High Levels Talents Cultivation of Jiangsu Province.
作者简介
Address correspondence to:Shangpeng Sun,shangpeng.sun@mcgill.ca;Address correspondence to:Ni Ren,rn@jaas.ac.cn
