Recognition of flowers using convolutional neural networks
by Abdulrahman Alkhonin; Abdulelah Almutairi; Abdulmajeed Alburaidi; Abdul Khader Jilani Saudagar
International Journal of Intelligent Engineering Informatics (IJIEI), Vol. 8, No. 3, 2020

Abstract: 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%.

Online publication date: Mon, 16-Nov-2020

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Engineering Informatics (IJIEI):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email