Ensemble Machine Learning Approach for Biological Bird Species Detection and Classification

Due to different ecological balances, there is need to identify the bird species which are varied from multiple locations. This research utilizes a novel ensemble platform, which combines Convolutional Neural Network (CNN), Support Vector Machine (SVM), and Random Forest models to categorize various bird species from various images. The literature survey focusses on various techniques to overcome the difficulties of bird species identification based on traditional recognition models. By integrating CNN, SVM, and Random Forest models - a hybrid model - achieved a 97% accuracy.