ASBTRACT

• 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.

EXISTING SYSTEM

• 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.

PROPOSED SYSTEM

• 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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