Bird_Species_Classification

This is a project developed for the curricular unit of Soft Computing.

Problem Statment

Classify the bird species that appear on an image based on the use of a Convolutional Neural Network model (CNN).

Learning Objectives

• Preparation and analysis of dataset;
• Training and validation of learning models, specifically Convolutional Neural Networks (CNN);
• Use of Genetic Algorithms (GA) for learning model hyper parameter optimization, structure optimization and loss function optimization.

Dataset

The proposed dataset has the following features:

• Bird Species: 250
• Training Images: 35215 (not balanced, however has at least 100 training image files per species);
• Validation Images: 1250 (5 per species);
• Test Images: 1250 (5 per species);
• Images Size: 224 x 224 x 3 color channels in jpg format;
• Species gender: 80% of total images are of male while the remaining 20% are of female - the classifier may not perform as well on female specie images.