Survey on Real Time Fruit Detection and Classification using Image Processing and Convolution Neural Network

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ISSN: 2349-6002 ESTD Year: 2014

UGC approved journal no 47859

Survey on Real Time Fruit Detection and Classification using Image Processing and Convolution Neural Network
Author(s):
Charan G, Ganesh P, Dheeraj M S, Dr. P N Sudha
Keywords:
Fruit Classification, Calorie Estimation, Convolution Neural Network (CNN), Deep learning, Raspberry pi, YOLO V4, Image Processing, Image Segmentation
Abstract
Fruit classification is an important task for many industrial applications. Image recognition and classification using Convolution Neural Networks (CNN) are the two popular approaches used in object recognition systems. The advancements in deep learning-based models make it possible to recognize complex images. This paper proposes an efficient CNN based method that performs fruit recognition, Raw-Ripe classification, calorie estimation and provide the count of the fruits from an input image. Machine learning model needs to be trained using data-sets. The data-set used are various image data containing different variety of fruit.
Article Details
Unique Paper ID: 154581 Publication Volume & Issue: Volume 8, Issue 11 Page(s): 617 - 622
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