ABSTRACT
This chapter presents the feasibility of using transfer learning to identify the change process of a fresh pepper. It identifies the change process of the pepper with the help of pre-trained model. There are many methods to identify the quality of fruits and vegetables. For example, the image processing technology has been widely used in agricultural products inspection and gradings, such as cereal grain color, grain shape, and type identification; fruit shape and defects; and other exterior quality inspection. Transfer learning has greatly reduced the workload of image acquisition, enabling the small datasets to achieve higher recognition accuracy. The model is pre-trained by using image-net dataset, and the data is imported into the model. Deep learning constitutes a modern technique for image processing and data analysis, with promising results and large potential. As deep learning has been successfully applied in various domains, it has also entered the domain of agriculture.
