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Home / Archives / Volume-4 / Issue-2 / Article-6

Volume - 4 | Issue - 2 | june 2022

Survey Paper on Fruit Recognition, Classification and Quality Health Maintenance
Sanketa Kulkarni  , V. S. Krushnasamy
Pages: 106-112
Cite this article
Kulkarni, S. & Krushnasamy, V. S. (2022). Survey Paper on Fruit Recognition, Classification and Quality Health Maintenance. Journal of Trends in Computer Science and Smart Technology, 4(2), 106-112. doi:10.36548/jtcsst.2022.2.006
Published
22 July, 2022
Abstract

This research focuses on fruit and vegetables classification, recognition based on its health and quality by using Raspberry pi board, which is further integrated with digital image processing techniques and machine learning concepts. Convolutional Neural Networks (CNN) is generally used to perform image identification and categorization in the object recognition systems. The recent advancements in deep learning-based models assist in performing complex image recognition. This study also proposes an effective CNN-based method for performing fruit recognition, fruit maturity based categorization, and calorie estimation. Datasets are used to train the proposed machine learning model. The dataset used here is a combination of image data containing various types of fruit; here the proposed cost-effective yet powerful fruit quality maintenance method will be useful for fruit vendors and farmers.

Keywords

Convolution neural networks raw-ripe raspberry pi machine learning image recognition.

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