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mega-project.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta http-equiv="X-UA-Compatible" content="ie=edge">
<title>Mega Project | IEEE BIT Mesra</title>
<link rel="stylesheet" href="resources/css/mega-project.css">
<link href="https://fonts.googleapis.com/css?family=Montserrat|Roboto+Condensed" rel="stylesheet">
</head>
<body>
<div class="container">
<div class="header">
<h1>IEEE Mega Project</h1>
</div>
<div class="text">
<p>IEEE mega project is a competition started to encourage study and research on new topics by the students. Students work on a topic which they themselves choose for around a semester and present it in the form of a report. Winners are decided based on presentation, content and innovation.</p>
<p>Some projects from the previous edition of 'Mega Project' are :
</p>
<br>
</div>
<div class="cards">
<div class="blog-card">
<div class="meta">
<div class="photo" style="background-image: url(resources/images/mega-project/1.jpg)"></div>
<ul class="details">
<li style="font-size: 40px;"><a href="https://github.com/KevinMathewT/Chatbot-Tensorflow" target="_blank"><i class="fa fa-github" aria-hidden="true"></i></a></li>
</ul>
</div>
<div class="description">
<h1>ChatBot</h1>
<h2>Kevin Mathew</h2>
<p>A Chatbot is an Artificial Intelligence which is designed to mimic how a person would behave as a conversational partner. For this project, a Seq2Seq model with Embedding and Attention Mechanism was used, which is the backbone of Google Translate. A Neural Network is a system which learns to perform a specific task by considering examples and learning from its mistakes. The Seq2Seq model consists of two Recurrent Neural Networks - one which decodes the meaning of the question asked by the user, represented by a thought vector, while the other attempts to give a meaningful reply based on the meaning decoded. The model learnt how to reply from a dataset of over 48,000 fictional conversations from over 600 movies. For the end product, the Deep Learning model was integrated with WhatsApp and had the ability to reply to messages coming from any source to the user’s mobile device</p>
<p class="read-more">
<a href="https://github.com/KevinMathewT/Chatbot-Tensorflow" target="_blank">Open in GitHub</a>
</p>
</div>
</div>
<div class="blog-card alt">
<div class="meta">
<div class="photo" style="background-image: url(resources/images/mega-project/2.jpg)"></div>
<ul class="details">
<li style="font-size: 40px;"><a href="https://github.com/rpuneet/Project-Handler?files=1" target="_blank"><i class="fa fa-github" aria-hidden="true"></i></a></li>
</ul>
</div>
<div class="description">
<h1>Project Handler</h1>
<h2>Puneet Rai</h2>
<p>Project Handler is a project organizing software which can help you keep track of your project, how much work is done? What is there that has to be done? Who is working on which part of the project? It supports multiple users, so multiple users can contribute to a single project. The software also stores each update to the project using git and makes it easier to go to any previous state if a problem arises. You can create, organize, manage and contribute to different projects.</p>
<p class="read-more">
<a href="https://github.com/rpuneet/Project-Handler?files=1" target="_blank">Open in GitHub</a>
</p>
</div>
</div>
<div class="blog-card">
<div class="meta">
<div class="photo" style="background-image: url(resources/images/mega-project/3.jpg)"></div>
<ul class="details">
<li style="font-size: 40px;"><a href="https://github.com/shiksha11/Jarvis4downloads" target="_blank"><i class="fa fa-github" aria-hidden="true"></i></a></li>
</ul>
</div>
<div class="description">
<h1>File Path Finder</h1>
<h2>Shiksha Rawat</h2>
<p>I developed a python based software to find paths of different files.This software takes file name as input from the user and displays it’s location as output.
One can get the output even when the file name is misspelled, incomplete or words are not in proper order.
File path can be found even by using words from the body of the file as input.
Input can be given in Audio form too.
I used Python modules like tkinter, pyaudio, csv,docx and pypdf2.</p>
<p class="read-more">
<a href="https://github.com/shiksha11/Jarvis4downloads" target="_blank">Open in GitHub</a>
</p>
</div>
</div>
<div class="blog-card alt">
<div class="meta">
<div class="photo" style="background-image: url(resources/images/mega-project/4.jpg)"></div>
<ul class="details">
<li style="font-size: 40px;"><a href="https://github.com/ygyash/PC-to-Phone-Transfer-using-QR-Code" target="_blank"><i class="fa fa-github" aria-hidden="true"></i></a></li>
</ul>
</div>
<div class="description">
<h1>Share files using QR code</h1>
<h2>Yash Goyal</h2>
<p>In order to easily transfer a file from web to any platform that reads a QR code, this project creates a link for the file and creates a QR code of the link. This link can be scanned through the QR scanner. The catch here is that the server and the device should be on the same network to download the file. Node.js has been used to create back-end of this project. Node module 'formidable' was used to upload the file on the server. An API was used to generate the QR code of the link. Bootstrap template 'Grayscale' has been used for front end.</p>
<p class="read-more">
<a href="https://github.com/ygyash/PC-to-Phone-Transfer-using-QR-Code" target="_blank">Open in GitHub</a>
</p>
</div>
</div>
<div class="blog-card">
<div class="meta">
<div class="photo" style="background-image: url(resources/images/mega-project/5.jpg)"></div>
<ul class="details">
<li><a href="#"></a></li>
</ul>
</div>
<div class="description">
<h1>Ultrasonic radar</h1>
<h2>Vivek Raj Gupta</h2>
<p>This project includes the integration of Arduino and Processing IDE to form a radar.
The Arduino sends the data( Distance and angle) to the processing through serial communication, thus displaying its position on radar and the buzzer goes on according to the distance of the object.</p>
<p class="read-more">
<a href="#"></a>
</p>
</div>
</div>
<div class="blog-card alt">
<div class="meta">
<div class="photo" style="background-image: url(resources/images/mega-project/6.jpg)"></div>
<ul class="details">
<li style="font-size: 40px;"><a href="https://github.com/aayushbhaskar/Indian-Music-Genre-Recognition" target="_blank"><i class="fa fa-github" aria-hidden="true"></i></a></li>
</ul>
</div>
<div class="description">
<h1>Music Genre Recognition</h1>
<h2>Aayush, Shivam</h2>
<p>This project is a take at the music genre recognition using machine learning, aimed at Indian music genres. The dataset used for the project was collected from various sources, and made into 30s .wav clips for training. They were converted into feature vectors uisng Fast Fourier Transform (FFT) method. Finally the model was trained using ANN, so that it could differentiate between various genres like Bolly Pop, Sufi, Ghazal, Carnatic and Hindustani Classical.</p>
<p class="read-more">
<a href="https://github.com/aayushbhaskar/Indian-Music-Genre-Recognition" target="_blank">Open in GitHub</a>
</p>
</div>
</div>
</div>
</div>
</body>
</html>