DCGAN-Based Data Augmentation for Tomato Leaf Disease Identification

DCGAN-Based Data Augmentation for Tomato Leaf Disease Identification

₹5,500.00
Product Code: Python - Deep Learning
Availability: In Stock
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Product Description

Aim:

            To detect the plant leaf diseases using convolutional neural network for high accuracy detection

Synopsis:

            Plant diseases are a major threat to plant growth and crop yield and many researchers have expended substantial efforts on detecting plant diseases. Traditionally, visual examination by experts has been carried out to diagnose plant diseases and biological examination is the second option, if necessary. In recent years, through the development of computer technology, machine learning has been widely utilized to train and detect plant diseases and is a satisfactory alternative for the detection of plant diseases.It is easier to realize higher accuracy by using a deep learning approach that is based on convolution neural networks. In this proposed system a deep learning approach that is based on improved convolution neural networks (CNN) for the real-time detection of plant leaf diseases.The proposed deep-learning based approach can automatically identify the discriminative features of the diseased plant images and detect the types of plant leaf diseases with high accuracy.


Proposed System:

            In this proposed system a deep learning approach that is based on improved convolution neural networks (CNN) for the real-time detection of plant leaf diseases. The proposed deep-learning based approach can automatically identify the discriminative features of the diseased plant images and detect the types of plant leaf diseases with high accuracy. At the same time the proposed approachcan detect not only various diseases in the same diseased image but also the same disease of different sizes in the same diseased image.

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Package Includes

Software Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
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  7. Source Code
  8. Screen Shots
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  10. Reference Papers
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The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days

 

Hardware Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. Datasheets
  6. Circuit Diagrams
  7. Source Code
  8. Screen Shots & Photos
  9. Software Links
  10. Reference Papers
  11. Lit survey
  12. Full Project Documentation
  13. Online support


The Delivery time for Hardware projects is 7-8 working days.

   

Mini Projects: Software Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support

 

The Delivery time for software Miniprojects is 2 -3 working days.

 

Mini Projects - Hardware includes

  1. Demo  Video
  2. Abstract
  3. PPT
  4. Datasheets
  5. Circuit Diagrams
  6. Source Code
  7. Screen Shots & Photos
  8. Software Links
  9. Reference Papers
  10. Full Project Documentation
  11. Online support

The Delivery time for Hardware Mini projects is 7-8 working days.