Animal Species Classification Using Deep Learning

This paper dives into the domain of animal image classification using deep learning methodologies, focusing on developing a robust model which would be able to accurately identify diverse animal species based on their visual characteristics. This project presents unique challenges owing to the wide variability in animal appearances, including differences in pose, body features, scale, occlusion, and environmental contexts. To cope up with these challenges there is need to design or create a deep learning model which can easily learn layered depiction of visual data. For this project we have created a model that can distinguish different animals from their image only. We have also used a pre-trained model known as EfficientNetB3 so as to make the model more efficient and increase its accuracy.