Automated Bird Detection using using Snapshot Ensemble of Deep Learning Models

A diverse variety of bird species are found in the earth. There are about 10,000 unique species of birds discovered so far. Identification and documentation of these birds, their migrating seasons, breeding seasons, food style, etc. requires effective monitoring. Identification of these birds is literally an impossible task for human without technological intervention. Hence deep learning models have been used which helps us in identification of the individual species of birds. In this scenario, it would be important to use an automated method to identify the species of birds. Several deep learning-based models for classifying and identifying bird species are evaluated in this study. These models are trained and tested on publicly available dataset. Snapshot images captured by the cameras are used as the major source of input data. The capability of deep learning models have been used to effectively identify the bird species individually. This study aims in developing a deep learning model using ensemble learning techniques that is capable of identification of individual bird species from a massive collection of input data images.