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12 Wheat rust disease identification using deep learning

  • Sapna Nigam , Rajni Jain , Sudeep Marwaha and Alka Arora
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Internet of Things and Machine Learning in Agriculture
This chapter is in the book Internet of Things and Machine Learning in Agriculture

Abstract

Automated image-based tools are required when a human assessment of plant disease identification is expensive, inappropriate, or unreliable. Thus, there is a need to recognize cost-effective automated computational systems and imagebased tools for disease detection that would facilitate advancements in agriculture. Deep learning (DL) is the deep neural network that uses multiple levels of abstraction for hierarchical representation of the data. Convolutional neural network model is used, in this chapter, on 2,000 images to identify the wheat rust disease in an unseen leaf image. The results show that DL has the potential to identify plant diseases with much higher accuracy.

Abstract

Automated image-based tools are required when a human assessment of plant disease identification is expensive, inappropriate, or unreliable. Thus, there is a need to recognize cost-effective automated computational systems and imagebased tools for disease detection that would facilitate advancements in agriculture. Deep learning (DL) is the deep neural network that uses multiple levels of abstraction for hierarchical representation of the data. Convolutional neural network model is used, in this chapter, on 2,000 images to identify the wheat rust disease in an unseen leaf image. The results show that DL has the potential to identify plant diseases with much higher accuracy.

Chapters in this book

  1. Frontmatter I
  2. Preface VII
  3. Acknowledgments IX
  4. Contents XI
  5. List of contributors XIII
  6. Part I: Machine learning and Internet of things in agriculture
  7. 1 Smart farming: using IoT and machine learning techniques 3
  8. 2 Food security and farming through IoT and machine learning 21
  9. 3 An innovative combination for new agritechnological era 41
  10. 4 Recent advancements and challenges of artificial intelligence and IoT in agriculture 65
  11. 5 Technological impacts and challenges of advanced technologies in agriculture 83
  12. Part II: Applications of Internet of things in agriculture
  13. 6 IoT-based platform for smart farming – Kaa 109
  14. 7 Internet of things platform for smart farming 131
  15. 8 Internet of things platform for smart farming 159
  16. 9 Internet of things platform for smart farming 169
  17. Part III: Applications of machine learning in agriculture
  18. 10 Kisan-e-Mitra: a tool for soil quality analyzer and recommender system 205
  19. 11 Artificial intelligence for plant disease detection: past, present, and future 223
  20. 12 Wheat rust disease identification using deep learning 239
  21. 13 Image-based hibiscus plant disease detection using deep learning 251
  22. 14 Rainfall prediction by applying machine learning technique 275
  23. 15 Plant leaf disease classification based on feature selection and deep neural network 293
  24. 16 Using deep learning for image-based plant disease detection 323
  25. 17 Using deep learning for image-based plant disease detection 355
  26. 18 Using deep learning for image-based plant disease detection 369
  27. Index 403
https://doi.org/10.1515/9783110691276-012

Chapters in this book

  1. Frontmatter I
  2. Preface VII
  3. Acknowledgments IX
  4. Contents XI
  5. List of contributors XIII
  6. Part I: Machine learning and Internet of things in agriculture
  7. 1 Smart farming: using IoT and machine learning techniques 3
  8. 2 Food security and farming through IoT and machine learning 21
  9. 3 An innovative combination for new agritechnological era 41
  10. 4 Recent advancements and challenges of artificial intelligence and IoT in agriculture 65
  11. 5 Technological impacts and challenges of advanced technologies in agriculture 83
  12. Part II: Applications of Internet of things in agriculture
  13. 6 IoT-based platform for smart farming – Kaa 109
  14. 7 Internet of things platform for smart farming 131
  15. 8 Internet of things platform for smart farming 159
  16. 9 Internet of things platform for smart farming 169
  17. Part III: Applications of machine learning in agriculture
  18. 10 Kisan-e-Mitra: a tool for soil quality analyzer and recommender system 205
  19. 11 Artificial intelligence for plant disease detection: past, present, and future 223
  20. 12 Wheat rust disease identification using deep learning 239
  21. 13 Image-based hibiscus plant disease detection using deep learning 251
  22. 14 Rainfall prediction by applying machine learning technique 275
  23. 15 Plant leaf disease classification based on feature selection and deep neural network 293
  24. 16 Using deep learning for image-based plant disease detection 323
  25. 17 Using deep learning for image-based plant disease detection 355
  26. 18 Using deep learning for image-based plant disease detection 369
  27. Index 403
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