Pixel RL: Fully Convolutional Network with Reinforcement Learning for Image Processing

Pixel RL: Fully Convolutional Network with Reinforcement Learning for Image Processing

₹5,000.00
Product Code: Matlab-Digital Image Processing
Availability: In Stock
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Product Description

                                    Technology: Image Processing                                                                   Tool: MATLAB R2018a

Objective:

The main aim of this project is used to enhance the image by using deep learning techniques.

Abstract:

Deep learning has been achieving great success not only in image classification, but also in image processing tasks such as image filtering, colorization, generation, and translation. An effective learning method for the pixel RL problem, which boosts the performance of the pixel RL agents. Our experimental results demonstrated that the proposed method achieved comparable or better results than state-of-the-art methods on each application. An effective learning method for the pixel RL problem, which boosts the performance of the pixel RL agents. Our experimental results demonstrated that the proposed method achieved comparable or better results than state-of-the-art methods on each application. In the proposed system the median filter technique is applied in order to remove the noise from the input image. Dehazing algorithm based on the difference structure preservation prior, which can estimate the optimal transmission map and restore the actual scene. The method of image contrast enhancement on the basis of the contrast distribution at the boundaries of objects and background on the image is proposed.


Proposed System:

In the proposed system the median filter technique is applied in order to remove the noise from the input image. Dehazing algorithm based on the difference structure preservation prior, which can estimate the optimal transmission map and restore the actual scene. The method of image contrast enhancement on the basis of the contrast distribution at the boundaries of objects and background on the image is proposed.

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Package Includes

Software Projects 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 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.