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Deep Learning in Pest Identification by elstar724 is a document available to read on EtoBox.

This paper discusses the evolution of deep learning techniques, specifically convolutional neural networks (CNN) and Vision Transformers, in the identification of agricultural pests and diseases. It highlights the limitations of traditional machine learning methods and emphasizes the advantages of deep learning in terms of accuracy and generalization. The authors also address key challenges in the field and propose future research directions to enhance pest and disease identification technologies.

Author

elstar724

Language

EN