Harmandeep Singh Gill1,*, Osamah Ibrahim Khalaf2, Youseef Alotaibi3, Saleh Alghamdi4, Fawaz Alassery5
CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5135-5150, 2022, DOI:10.32604/cmc.2022.022809
Abstract Fruit classification is found to be one of the rising fields in computer and machine vision. Many deep learning-based procedures worked out so far to classify images may have some ill-posed issues. The performance of the classification scheme depends on the range of captured images, the volume of features, types of characters, choice of features from extracted features, and type of classifiers used. This paper aims to propose a novel deep learning approach consisting of Convolution Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) application to classify the fruit images. Classification accuracy depends on the extracted… More >
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