基于AlexNet的番茄生长周期智能辨别系统设计

Design of Tomato Growth Cycle Intelligent Identification System Based on AlexNet

针对目前国内计算机视觉和深度学习技术在农产品生长监控方面研究应用不足的问题,顺应现代农业科技发展潮流,基于AlexNet神经网络使用Python语言设计了一个番茄生长周期智能辨别系统。实验表明该系统可以对处于各个生长周期的番茄进行智能分类,具有较高使用价值。

Aiming at the problem that insufficient research and application of computer vision and deep learning technology in agricultural products growth monitoring in China,this paper conforms to the development trend of modern agricultural technology,and designs an intelligent identification system of tomato growth cycle based on AlexNet neural network using Python.Experiments show that this system can intelligently classify tomato in each growth cycle and has a high use value.