ABSTRACT
This chapter provides a diagnostic system based on transfer learning for pest detection and recognition. It aims to compare the transfer learning method with human experts and a traditional neural network model. Pest recognition is very important to crops growing healthily, and this in turn affects crop yields and quality. The pest problem is very complicated because of differences in soil type, weather conditions, cultivar, and so on. Transfer learning is very popular in the field of machine learning. From the relevant but different source domain, transfer learning can learn to apply knowledge and it can improve learning level on the target domain. AlexNet is a Convolutional Neural Network which won the ImageNet Large-Scale Visual Recognition Challenge, an annual challenge that is intended to evaluate algorithms for object detection and image classification. AlexNet is composed of eight trainable layers, five convolution layers, and three fully connected layers.
