Dog Breed Identification Using Deep Learning

Abstract

Deep learning has revolutionized computer vision tasks, including image classification. In this study, we propose a deep learning approach for the identification of dog breeds from images. Leveraging transfer learning with the ResNet50V2 model, our methodology involves preprocessing and augmenting a dataset of dog images to enhance model generalization. Through rigorous experimentation and training, our model achieves competitive accuracy rates in identifying over 60 unique dog breeds. Results indicate the efficacy of our approach in breed classification tasks, with potential applications in pet identification systems and animal welfare initiatives. Keywords: Deep learning, Dog breed identification, Transfer learning, Computer vision.