基于MobileNet的果蔬识别系统

Fruit and Vegetable Recognition System Based on MobileNet

我国疆域辽阔,土壤肥沃,气候温和,尤其是新疆地区,日照时间充足,盛产水果。造就了我国成为农业生产大国,每年进出口非常多的水果蔬菜。据了解,在大部分农贸市场都靠人工进行果蔬分类,工作量多且效率低下。提出一种基于MobileNet模型的果蔬识别系统,该系统可以快速进行果蔬识别。该项目用了传统CNN模型和更轻量化的MobileNet模型对12个不同品种的蔬果数据集进行训练,发现基于MobileNet模型的识别结果正确率更高。

China has a vast territory,fertile soil and mild climate.Especially in Xinjiang,it has sufficient sunshine and is rich in fruits.As a result,China has become a large agricultural production country,importing and exporting a lot of fruits and vegetables every year.It is understood that in most farmers’markets,fruits and vegetables are classified manually,which has a large of workload and low efficiency.Therefore,this paper puts forward a fruit and vegetable recognition system based on MobileNet model,which can quickly recognize fruits and vegetables.The project uses the traditional CNN model and the lighter MobileNet model to train the data sets of 12 different kinds of fruit and vegetable.It is found that the recognition result based on MobileNet model has a higher accuracy.