Identification of Cucumber Leaf Diseases Based on Transfer Learning

EasyChair Preprint 9208

Abstract

In this paper, a recognition framework of cucumber leaf diseases based on depth learning is proposed. In the feature extraction stage, the framework uses migration learning to train VGG19 and Inception V3 models, uses parallel maximization fusion method for information fusion, and uses whale optimization algorithm for feature optimization. In the final classification process, supervised learning algorithm is used to classify the selected best features. The experiment process is carried out on a self-made data set, which is composed of five cucumber diseases. The accuracy of the algorithm is 96.5%, and it takes 45.28 seconds

Keyphrases: Disease Identification, Transfer Learning, Whale Optimization Algorithm

@booklet{EasyChair:9208,
  author    = {Honghao Wu and Juan Sun and Huaixia Liu},
  title     = {Identification of Cucumber Leaf Diseases Based on Transfer Learning},
  howpublished = {EasyChair Preprint 9208},
  year      = {EasyChair, 2022}}