Classification of Ripening of Banana Fruit Using Convolutional Neural Networks

6 Pages Posted: 23 Mar 2020

See all articles by M. Kusuma Sri

M. Kusuma Sri

Anurag Group of Institutions

K. Saikrishna

Anurag Group of Institutions

V. Vinay Kumar

Anurag Group of Institutions

Date Written: February 21, 2020

Abstract

Many technological advancements have been developed for precise learning in every field. It is very important to analyse the data in order to extract some useful information. Machine learning and Deep Learning is an integral part of artificial intelligence, which is used to design algorithms based on the data trends and historical relationships between data. Machine learning is used in many fields but the most upgrading and preferred area in which this technology can be seen with value is agriculture. Machine Learning and Deep Neural Networks have made a significant footprint in agriculture area. To standardize the quality of bananas it is essential to determine ripening stages of bananas. This paper proposed a special Convolutional Neural Network architecture to classify the ripening of banana fruits correctly. It learns a set of image features based on a data-driven mechanism and offers a deep indicator of banana’s ripening stage.

Keywords: Banana images dataset, Deep Learning-CNN

JEL Classification: O30

Suggested Citation

Sri, M. Kusuma and Saikrishna, K. and Kumar, V. Vinay, Classification of Ripening of Banana Fruit Using Convolutional Neural Networks (February 21, 2020). Proceedings of the 4th International Conference: Innovative Advancement in Engineering & Technology (IAET) 2020, Available at SSRN: https://ssrn.com/abstract=3558355 or http://dx.doi.org/10.2139/ssrn.3558355

M. Kusuma Sri (Contact Author)

Anurag Group of Institutions ( email )

Hyderabad
India

K. Saikrishna

Anurag Group of Institutions ( email )

Hyderabad
India

V. Vinay Kumar

Anurag Group of Institutions ( email )

Hyderabad
India

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