Back to all projects
Computer Vision

Handwritten Digit Recognition

Classifying handwritten digits from the MNIST dataset using Random Forest ensemble learning.

View on GitHub
Handwritten Digit Recognition screenshot

Project Overview

An image classification project focused on identifying digits (0-9) using a collection of decision trees.

Technologies Used

PythonRandom ForestScikit-learn

Methodology

  1. 1Flattening 2D image arrays into feature vectors.
  2. 2Hyperparameter tuning for the number of estimators.
  3. 3Training a Random Forest classifier.
  4. 4Testing model robustess on unseen handwritten samples.

More in Computer Vision

Real Time Object Recognition

Detecting and tracking moving objects in video streams using computer vision techniques.

AI powered Face Detection and Tracking

Implementing real-time face detection and tracking in video feeds.

Advanced Real Time Multi-Color Object Tracking System

Tracking specific objects in video based on their color properties.