Image Classification Using Deep Neural Network

Image Classification is widely used in various fields such as Plant leaf disease classification, facial expression classification. To make bulky images handy, image classification is done using the concept of a deep neural network. The proposed work implemented the VGG16 model to classify an image into one of the categories like living and non-living that is further classified into several classes like an animal, human, selfie, group photos, place, wallpaper, vehicles, etc. The paper contributes a methodology for a more accurate classification of images instead of image feature extraction or image segmentation. The proposed work established a promising accuracy of 99.89%.