基于深度学习的苹果内部品质评价系统开发与设计OA

Apples are known as the king of fruits.With the increase in apple production in various provinces in the country,many apples suffering from internal defects such as mildew heart disease and bumps are also mixed in the market.Traditional manual identification can only detect the external quality of apples and cannot evaluate the internal quality.Based on the high cost of detection technologies such as infrared spectroscopy and CT scanning,ultrasound provides new ideas for non-destructive testing and grading of apple internal quality due to its low price and harmlessness to the environment.This paper proposes to carry out research on apple internal quality detection methods based on ultrasonic signal analysis and deep learning technology,and improve the ResNet18 model.The classification accuracy rate reaches 93.8%,and develop and design an apple internal quality detection system.