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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM25091

AUTOMATIC FRUIT DETECTION USING MULTILAYER NEURAL NETWORK

Stream/Area:

-

Subject:

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Paper ID:

10.55041/IJSREM25091

Volume:

7 |

8 |

Aug 2023

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

MCM

Manasa C M

DHSR

Dr. Hemanth S R

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Abstract

Agriculture has become an important thing in everyday life .Among this, fruits are a great thing in everyday life. Classification of fruits based on their accuracy is a decent approach to all the fruit sellers. There is much parallelism between apple and cherry and various kinds of similarities are present in many types of fruits, so the classification plays an important role. However, there are troubles in fruit classification using machine learning algorithms like Support Vector Machine (SVM) and Convolution Neural Network (CNN). So, the methods of CNN, pooling layers and fully connected network have been applied to overcome the problems. The CNN and pooling layers have been applied to extract the features of the fruits.

KEYWORDS

Agriculture Convolution Neural Network machine learning Support Vector Machine.

Cite This Article

Manasa C M, Dr. Hemanth S R, "AUTOMATIC FRUIT DETECTION USING MULTILAYER NEURAL NETWORK," International Journal of Scientific Research in Engineering and Management, vol. 7, no. 8, Aug 2023. https://doi.org/10.55041/IJSREM25091

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Publication Date

6/7/2023

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The authors declare no conflict of interest related to this research work.

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