Flower classification using CNN and transfer learning in CNN- Agriculture Perspective

Classification of flowers is a difficult task because of the huge number of flowering plant species, which are similar in shape, color and appearance. A flower classification can be used in various applications such as field monitoring, plant identification, medicinal plant, floriculture industry, research in plant taxonomy. In this study, the authors have demonstrated and analyzed the recent developments in deep learning methods such as CNN and transfer learning in CNN. Prototype CNN model architecture proposed and transfer learning approach as well examined on VGG16, MobileNet2 and Resnet50 architecture for flower classification on publicly available flower dataset.