Sign Language Letter Recognition Project

Overview

This project implements various artificial neural network techniques:

• the simple perceptron
• Perceptron using the gradient descent learning technique
• Perceptron using the ADALINE learning technique
• Single-layer perceptron
• Multi-layer perceptron

Project Structure

SignLanguageRecognition/
├── src/
│   ├── datas/                    # CSV
│   ├── perceptron/               # Directory with different perceptron
└── README.md                      # Project documentation

Web Application

The web application is implemented in app.py using Flask. It allows users to:

• Select kind of Algorithm and script.

How to Run

1. Clone the Repository

git clone <repository-url>
cd PerceptronMethods

2. Install Dependencies

Once your requirements.txt file is ready, you can install all the dependencies with a single command:

pip install -r requirements.txt

3. Run the Web Application

Start the Flask server to launch the web application:

python src/perceptron/app.py

• Open your browser and go to http://localhost:5000.
• Select Algorithm & script.

Collaborators

This project was developed by the following team members:

• Mathys Franco

• Cameron Noupoue

• Jobelin Kom