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about.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">
<title>RNDas Binary Recognizer</title>
<link rel="icon" type="image/x-icon" href="assets/img/favicon.ico">
<link rel="stylesheet" href="assets/css/aboutstyle.css">
<link rel="stylesheet" href= "https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.1.1/css/all.min.css" integrity="sha512-KfkfwYDsLkIlwQp6LFnl8zNdLGxu9YAA1QvwINks4PhcElQSvqcyVLLD9aMhXd13uQjoXtEKNosOWaZqXgel0g==" crossorigin="anonymous" referrerpolicy="no-referrer" />
<script src= "https://kit.fontawesome.com/c353d71a36.js" crossorigin="anonymous"></script>
<script async defer src="https://buttons.github.io/buttons.js"></script>
</head>
<body>
<nav class="navbar">
<div class="navbar-container">
<div class="navbar-logo">
<img src="assets/img/binary-code.png" alt="Logo">
<span style="font-family:'Segoe UI', Tahoma, Geneva, Verdana, sans-serif">RNDas Binary Recognizer</span>
</div>
<ul class="navbar-links">
<li><a href="/Binary-Recognizer/index.html">Home Page</a></li>
<li><a href="/Binary-Recognizer/tutorial.html">How to Use</a></li>
<li><a href="/Binary-Recognizer/about.html">About App</a></li>
<li><a href="https://rndastech.github.io/">About Me</a></li>
</ul>
<button class="contact-button" onclick="location.href='mailto:rndas2004@gmail.com'" type="button">Contact Me</button>
</div>
</nav>
<div class="container"><h1>About App</h1></div>
<div class="container">
<p style="font-family:'Gill Sans', 'Gill Sans MT', Calibri, 'Trebuchet MS', sans-serif">
RNDas Binary Recognizer is a powerful website designed to interpret and process handwritten symbols, focusing on binary digits 0 and 1, and a variety of mathematical symbols. Leveraging advanced deep learning techniques, specifically neural networks, the app delivers high accuracy in handwriting recognition. Users can write symbols and equations on their device’s screen, with the app capturing and processing the input. It accurately recognizes handwritten binary digits and mathematical symbols such as +, -, *, and ÷, allowing users to write out complete mathematical expressions effortlessly. Upon recognizing a complete expression, the app performs the specified operation, providing instant results. Utilizing TensorFlow Neural Networks for image recognition tasks, the app ensures precise interpretation of various handwriting styles. With an interactive and intuitive interface, and applications in both educational and practical contexts, RNDas Binary Recognizer seamlessly combines cutting-edge technology with practical functionality to make handwriting recognition and mathematical operations efficient and user-friendly.</p>
<img src="assets/img/binary-code.png" width="20%" height="20%" alt="ML Model Making A Prediction" style="margin-left: 20px; margin-right: 20px;">
</div>
</body>
<footer>
<footer style="font-family:Arial, Helvetica, sans-serif">
<div class="footer-container">
<div class="footer-section about">
<h2>About Me</h2>
<p>Specialist @ CodeForces<br>4* @ CodeChef<br>NTSE Scholar<br>IIIT Allahabad '27</p>
</div>
<div class="footer-section links">
<h2>Quick Links</h2>
<ul>
<li><a href="/Binary-Recognizer/index.html">Home Page</a></li>
<li><a href="https://rndastech.github.io/">About Me</a></li>
<li><a href="https://github.com/rndastech">GitHub</a></li>
<li><a href="https://codeforces.com/profile/rn_das_2004">CodeForces</a></li>
</ul>
</div>
<div class="footer-section social">
<h2>Follow Me</h2>
<div class="social-links">
<a href="https://github.com/rndastech"><i class="fab fa-github"></i></a>
<a href="https://www.instagram.com/rndascode/"><i class="fab fa-instagram"></i></a>
<a href="https://www.linkedin.com/in/ritesh-narayan-das-6196b3268/"><i class="fab fa-linkedin-in"></i></a>
</div>
</div>
</div>
<div class="footer-bottom">
© 2024 Ritesh Narayan Das
</div>
</footer>
</footer>
</html>