Recognition of flowers using convolutional neural networks. (3rd November 2020) - Alkhonin, Abdulrahman; Almutairi, Abdulelah; Alburaidi, Abdulmajeed; Saudagar, Abdul Khader Jilani
Every human has curiosity about what's around them. Most of the people love the nature and visits different places like parks, flower shows etc., with family and children during free time. But due to lack of enough knowledge and information it is very difficult to decide which flowers are beneficial, non-poisonous and edible to mankind. To solve this problem, this work developed a mobile application which capture flower images and helps in recognising the flowers and categorise them into different categories using deep learning algorithms. This work uses a dataset which contains four different flowers (Sunflower, Dandelion, Rose, and Tulip) for training purpose and tested with a sample of flowers over the trained model. The percentage of overall accuracy achieved in recognition of flowers is approximately 83.13%.