Birds Species Identification Using Deep Learning Model

This analysis's goals are to identify and categorize a broad variety of bird species and to provide an improved approach to supplement the current ones. This system uses a preprocessed dataset to evaluate and train on several bird species, such as owls, robins, and eagles, in addition to an unidentified bird category. To guarantee the highest level of precision, species identification accuracy is carefully evaluated using a confusion matrix. The accuracy of each approach used for bird identification is used to rank them according to species recognition. This work emphasizes the value of quickly and precisely identifying bird species in order to enhance the experience of birdwatching, and it also emphasizes the contribution of computer-aided models to increased precision. The suggested method's astounding accuracy of 97.21% was attained.