kunal2812 / Mini-Project

Mini Project

Introduction:

This repository is for our semester mini project on machine learning and visual cryptography.

This repository will contains all the code, data, and documentation related to our project, including the implementation of the machine learning models and the visual cryptography algorithms, as well as sample datasets and instructions on how to run the code.

Task 1

Verify the results using some image from the ensemble model in given repository.

Covid-19 Detection Using Ensembling

Result

Task 2

Extract the features from any three models and apply features selector algorithms - ReliefF and Chi2 on it. Then use the selected features for classification using Decision Tree and Support Vector Machines.

Dataset

Task 3

Combine features from different models (Ensemble) and use ReliefF on them.

Dataset

Reference Notebook

Task 4

Implement image encryption using hyperchaotic maps (Logistic Map).

Results

• Encrypted

• Decrypted

Task 5

Implement image encryption using DNA Algorithm.

Task 6

Implement and fix majority voting in the given repository.

Grape Disease Classification

Dataset

Reference Repo

Task 7

Implement a efficient and strong encryption algorithm with high non linearity using concepts like S Boxes, Dynamic Permutation and Grey Wolf Algorithm.

Project Repo:

Github

References:

1. Image encryption algorithm using dynamic permutation and large chaotic S-box

2. New color image encryption technique based on three-dimensional logistic map and Grey wolf optimization based generated substitution boxes

Technology Stack:

1. Tensorflow
2. Keras

Contributors:

• Kunal Katiyar
• Nandini Karad
• Lakshay
• Prince Verma