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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">
<title>20093701</title>
<link rel="stylesheet" href="stylesheet.css">
</head>
<body>
<nav>
<ul>
<li><a href="index.html">Home</a></li>
<li><a href="about.html">Extra</a></li>
</ul>
</nav>
<header>
<h1>Dog Breed Identification System using Image Classification with web app interface.</h1>
<h2>Dog Breed Identifier</h2>
</header>
<main>
<section>
<img class="right-aligned" src="portrait.jpg" alt="portrait photo" width="40%" height="40%">
<h2>About Me</h2>
<ul>
<li><b>Name: </b>Dominik Kawka</li>
<li><b>Student Number: </b>20093701</li>
</ul>
</section>
<section>
<h2>Project Description</h2>
<p>The goal of this project is to build a Machine Learning model capable of differentiating between different dog breeds. The user will be able to upload photos of their dog via a web app, which will then be fed into the model, returning the predicted breed, along with extra info.</p>
<br>
<p>If the predicted breed is incorrect, the user may submit feedback by submitting the correct breed. These images will be used to further train the model. If the user has an account, they can view their history of previously submissions.</p>
<br>
<p>The project follows an agile-scrum workflow, breaking the project down into 2 week sprints, using Gantt charts as a general outline of the entire development process.</p>
<br>
<p>Users of this app may find out more about their pets, and characteristics of their dogs breed, which may lead to better informed decisions regarding pet ownership and health.</p>
</section>
</main>
<footer>
<p>Dominik Kawka W20093701</p>
</footer>
</body>
</html>