Classification of Bird Species Using Deep Learning Techniques

Abstract: Nowadays some bird species are not being located often than we used to see them in our childhood and if we do observed them we can’t predict the type of bird species as it is very hard to predict as we haven’t familiar enough with them. naturally, birds found in numerous situations appear in one-of-a-kind sizes, shapes, coloring, and angles from the human perspective. except, the robust to discover the bird species extra than audio category. additionally, the human capability to apprehend the birds through the photos is more comprehensible. So, this approach makes use of the dataets made by many researchersa and bird enthusiasts for schooling also in addition to testing purposes. through the usage of a convolutional neural network (CNN) basically set of rules a photo that is converted into a greyscale layout to generate an autograph via the usage of tensor-flow, where the multiple nodes of comparison are generated. those different nodes are compared with the traing and testing dataset and a score sheet is received from it. After reading the datasheet describing the accuracy of our proposed trained model, it can predicate the desired species with the aid of using the highest precision we could get. Experimental evaluation at the dataset shows that the algorithm achieves an accuracy of identity among 86% to 87% The experimental observed is accomplished with visual studio book with the usage of a Tensor flow library.