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Deep Learning for Fruit Quality Prediction by stellarosemalar is a document available to read on EtoBox.

This research paper discusses the development of deep learning models for predicting fruit quality, focusing on the use of Convolutional Neural Networks (CNN) and transfer learning to classify fresh and rotten fruits. The proposed models achieved high accuracy rates of 99.39% on training data and 99.99% on validation data, demonstrating their effectiveness in real-time agricultural applications. The study highlights the need for automated fruit grading systems to improve efficiency and reduce labor in the a

Author

stellarosemalar

Language

EN