Using the notion of deep learning, the research aims to construct a model for the identification and categorization of fruits. The idea is to use convolutional neural networks to construct an automated feature extraction method. Fruit recognition is utilised in a variety of agricultural applications, including robot harvesting and fruit counting, among others. The system has the ability to sort the fruits. It may be used to examine the condition of fruits and evaluate whether or not they are fresh. Fruits can be recognised utilising the retail store's self-service technology. The recommended solution makes advantage of the high-quality 'ImageNet' dataset. The collection's fruit photos are organised into five categories. The data set is difficult to work with since the photos feature a variety of fruits of the same colour, shape, and size, and the fruits are overlapping. To distinguish fruits from photos, the model use Convolutional Neural Networks. It was discovered that the accuracy was 92.23 percent. Deep learning algorithms surpass machine learning algorithms.
Author(S) Details
Deepali M. Bongulwar
Department of Electronics and Communication, Sri Satya Sai University of Technology and Medical Sciences, Sehore (MP), India.
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