A Comprehensive Analysis of Deep Learning Techniques for Recognition of Flower Species

Abstract

Flower Species Recognition may be a difficult issue due to the wide selection of features, like leaves and grass. The classification is done by the traditional method through color, shape, texture, petals, sepals etc. The image analysis and classification has been sharply developed by Deep Learning methods. This research work considered a dataset which contains 4242 images with 5 classes by using Convolutional Neural Network (CNN) to recognize flower species with high accuracy by using framework. Tensor Flow and Image Data Generator is used to augment the training set and avoid Overfitting.