• In this project, we propose an intelligent system to detect and distinguish Vitamin Deficiency from Human Tissue by deep learning techniques.
  • At first, image clustering into segment out the lesion.
  • Our aim is to test the effectiveness of the proposed segmentation technique, extract the most suitable features, and compare the classification results with the other techniques
  • Deep neural network is utilized for the classification of Stomach cancer Images.


  • Human based systems are involved in the Vitamin Deficiency Detection process.
  • But this type of systems are having reliably issues with man made error chances.
  • The most commonly used technique SVM is not a straightforward task due to the great variety of Tissues, low contrast between the lesion and the surrounding Stomach, irregular and fuzzy lesion borders Skin Images types and presence of Noise.


  • In this project, an approach to border detection in Tissue images based on the multi-level decomposition and classification method is presented.
  • The scope of ALEXNET is used.
  • Two phases are training and testing Done using Deep Neural Network.
  • Special camera called Microscopy camera’
  • is used for taking images.
  • An image is made up of a finite no of elements called pixels, each of which has a particular location and values.
  • Images are represented in the form of matrix in Python.
  • Classification is done using an ‘Reginal Convolutional neural network’
  • ‘ALEXNET is a mathematical or computational model and consists of an interconnected group of artificial neurons.
  • Two layer network is developed and training is done to achieve minimum error.



Software Requirements:

  • Front End – Anaconda IDE
  • Backend – SQL
  • Language – Python 3.8

Hardware Requirements

  • •Hard Disk: Greater than 500 GB
  • •RAM: Greater than 4 GB
  • •Processor: I3 and Above

Including Packages


  • * Base Paper
  • * Complete Source Code
  • * Complete Documentation
  • * Complete Presentation Slides
  • * Flow Diagram
  • * Database File
  • * Screenshots
  • * Execution Procedure
  • * Readme File
  • * Addons
  • * Video Tutorials
  • * Supporting Softwares

Specialization =======================

  • * 24/7 Support * Ticketing System
  • * Voice Conference
  • * Video On Demand 
  • * Remote Connectivity
  • * Code Customization
  • * Document Customization 
  • * Live Chat Support

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