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Classification of Ripening of Banana Fruit Using Convolutional Neural Networks

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Document pages: 6 pages

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.

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