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Deep Learning for Agricultural Visual Perception Crop Pest and Disease Detection /

This monograph provides a detailed and systematic introduction to the application of deep learning technology in the intelligent monitoring of crop diseases and pests. Taking 24 types of crop pests, wheat aphids, and wheat diseases with complex backgrounds as examples, a large-scale crop pest and di...

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Detalles Bibliográficos
Main Authors: Wang, Rujing (Author), Jiao, Lin (Author), Liu, Kang (Author)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:inglés
Publicado: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Edición:1st ed. 2023.
Subjects:
Artificial intelligence.
Image processing > Digital techniques.
Computer vision.
Machine learning.
Image processing.
Agriculture.
Artificial Intelligence.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Computer Vision.
Machine Learning.
Image Processing.
Acceso en liña:https://doi.org/10.1007/978-981-99-4973-1
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Table of Contents:
  • Chapter 1. Introduction
  • Chapter 2. Deep Learning Technology
  • Chapter 3. Large-Scale Agricultural Pest and Disease Datasets
  • Chapter 4. Sampling-balanced Region Proposal Network for Pest Detection
  • Chapter 5. Crop Pest Detection Methods in Field
  • Chapter 6. A CNN-based Arbitrary-oriented Wheat Disease Detection Method.

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