Hand Gesture Recognition

A computer vision project for hand gesture recognition using convolutional neural networks and transfer learning.

Overview

This project explores image-based hand gesture recognition using deep learning models. The main objective is to classify hand gestures from images and investigate the use of pretrained convolutional neural networks for visual recognition.

The project is implemented in a Jupyter Notebook and includes experiments with MobileNet-based architectures.

Approach

The overall workflow is:

Input Images
     │
     ▼
Image Preprocessing
     │
     ▼
Data Preparation
     │
     ▼
CNN / Transfer Learning
     │
     ├── MobileNet
     └── MobileNetV2
     │
     ▼
Gesture Classification
     │
     ▼
Prediction