Deep Convolutional Neural Network for Automated Bird Species Classification

Abstract

Birds significantly contribute to ecosystem maintenance, involving seed dispersion, air oxygenation, contaminant conversion into nutrients, and climate regulation. However, with over ten thousand bird species described globally, accurate identification based solely on their appearances poses a challenge, even for experienced bird watchers, leading to potential discrepancies in species classification. This difficulty highlights the challenges that both human intelligence and artificial intelligence encounter when accurately identifying bird species. To address this challenge, we propose an automatic bird species classification system using deep learning techniques. Our study leverages the power of deep learning in computer vision to assist novice bird enthusiasts in accurately identifying the plethora of bird species they encounter. We gathered and utilized a diverse dataset of bird images to train a convolutional neural network (CNN) model. Our classification system, developed through training and careful evaluation has shown accuracy, in identifying different bird species using images. This system serves as a tool in real world situations allowing bird enthusiasts to gain an appreciation for the diverse range of avian species and actively contribute to conservation efforts. Our classification system, which has been extensively trained and thoroughly evaluated has proven to be highly accurate, in identifying bird species based on images. It provides a tool for bird enthusiasts to truly appreciate the range of avian species and contribute to conservation efforts. Our research introduces an efficient approach, based on learning for automatically classifying bird species from images. This addresses the challenges faced by both experts and non experts in identifying birds. Our designed deep convolutional neural network (DCNN) achieved an accuracy rate of 92% ensuring precise recognition of various species. This system plays a role in preserving and comprehending bird ecosystems emphasizing their contribution, to maintaining global landscapes and climate stability.