ABSTRACT
Many technological advancements have been developed for precise learning in every field. It is very important to analyze the data in order to extract some useful information. To standardize the quality of bananas it is essential to determine grade of bananas. This project present a Convolutional Neural Network architecture to classify the grade 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 grade. The computer vision techniques can potentially provide an automated and non-destructive tool for the classification of grading banana. In the field of artificial intelligence, recent advances in deep learning have led to breakthroughs in long-standing tasks such as vision-related problems of feature extraction, image segmentation, and image classification. Among all these techniques, convolutional neural network (CNN) is one of the most successful methods and has acquired a broad application in image classification. The process of transforming photos into the appropriate digital image data in order to extract particular information is known as image processing. Image processing refers to a strategy or approach for processing photos or images by modifying the chosen image data to get accurate information. Processing a picture is made simple by image processing. Utilizing tried-and-true image processing technologies helps increase fruit grading system. This project is developed in matlab using convolutional neural network in image processing.
PROJECT OUTPUT
PROJECT DEMO VIDEO
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