Redirigiendo al acceso original de articulo en 20 segundos...
Inicio  /  Agriculture  /  Vol: 13 Par: 11 (2023)  /  Artículo
ARTÍCULO
TITULO

Application of Vision Technology and Artificial Intelligence in Smart Farming

Xiuguo Zou    
Zheng Liu    
Xiaochen Zhu    
Wentian Zhang    
Yan Qian and Yuhua Li    

Resumen

No disponible

 Artículos similares

       
 
Guangyu Hou, Haihua Chen, Mingkun Jiang and Runxin Niu    
Intelligent agriculture imposes higher requirements on the recognition and localization of fruit and vegetable picking robots. Due to its unique visual information and relatively low hardware cost, machine vision is widely applied in the recognition and ... ver más
Revista: Agriculture

 
Dmitriy Yu. Pavkin, Evgeniy A. Nikitin, Denis V. Shilin, Mikhail V. Belyakov, Ilya A. Golyshkov, Stanislav Mikhailichenko and Ekaterina Chepurina    
Practical experience demonstrates that the development of agriculture is following the path of automating and robotizing operational processes. The operation of feed pushing in the feeding alley is an integral part of the feeding process and significantl... ver más
Revista: Agriculture

 
Xuan Li, Mengyuan Yu, Dihong Xu, Shuhong Zhao, Hequn Tan and Xiaolei Liu    
Backfat thickness (BF) is closely related to the service life and reproductive performance of sows. The dynamic monitoring of sows? BF is a critical part of the production process in large-scale pig farms. This study proposed the application of a hybrid ... ver más
Revista: Agriculture

 
Hua Yang, Xingquan Deng, Hao Shen, Qingfeng Lei, Shuxiang Zhang and Neng Liu    
In recent years, the domain of diagnosing plant afflictions has predominantly relied upon the utilization of deep learning techniques for classifying images of diseased specimens; however, these classification algorithms remain insufficient for instances... ver más
Revista: Agriculture

 
Meixiang Chen, Liping Chen, Tongchuan Yi, Ruirui Zhang, Lang Xia, Cheng Qu, Gang Xu, Weijia Wang, Chenchen Ding, Qing Tang and Mingqi Wu    
Traditional traps for Spodoptera frugiperda (J. E. Smith) monitoring require manual counting, which is time-consuming and laborious. Automatic monitoring devices based on machine vision for pests captured by sex pheromone lures have the problems of large... ver más
Revista: Agriculture