Identification of Dog Breeds Using Deep Learning

Abstract

In this forecourt competition, we are provided a stringently mongrel division of ImageNet in order to exercise fine-grained image cataloguing. The dataset contains images of dogs of different breeds. Deep Learning is a technique by which a computer program learns statistical patterns within the data that will enable it to recognize or help us to distinguish between the different breeds of dogs. The model trains itself on the different features based on the images present and represent the data numerically, organizing the data in space. Initially, the image is divided into numerous lattices and a training batch size is set accordingly, then an algorithm is used to split and combine the descriptors, and the channel information of the image is extracted as the input of the convolutional neural network and finally, we design a convolutional neural network-based to identify the dog species. © 2019 IEEE.