Bird-Species-Identifiaction-from-Image

Now a days some bird species are being found rarely and if found classification of bird species prediction is difficult. Naturally, birds present in various scenarios appear in different sizes, shapes, colors, and angles from human perspective. Besides, the images present strong variations to identify the bird species more than audio classification. Also, human ability to recognize the birds through the images is more understandable. So this method uses the Caltech-UCSD Birds 200 [CUB-200-2011] dataset for training as well as testing purpose. By using deep convolutional neural network (DCNN) algorithm animage converted into grey scale format to generate autograph by using tensor flow, where the multiple nodes of comparison are generated. By establishing the database of standard images features for bird species and using the algorithm of similarity comparison, this system is proved to achieve good results in practice