Prediction of Pineapple Sweetness from Images Using Convolutional Neural Network

Adisak Sangsongfa, Nopadol Am-Dee, Payung Meesad
2018 EAI Endorsed Transactions on Context-aware Systems and Applications  
The objective of this research is to propose a deep learning based-prediction model for pineapple sweetness. In this research, we use a Convolutional Neural Network (CNN) to predict sweetness of pineapples from images. The dataset contains 4,860 pineapple images for training. Based on the CNN designed it is found that the best image size is 300 × 300 pixels resized to 30 × 30 pixels. The classification accuracy of training and testing are 72.38% and 78.50%, respectively. In addition, the root
more » ... ddition, the root mean square error values for training and testing are 0.1362 and 0.1156, respectively. When developed as a mobile application, the accuracy of the application is 80.15%, the root mean square error value is 0.0156 and the reliability is 95.00%
doi:10.4108/eai.13-7-2018.165518 fatcat:7qnubeobxja5vdofzmkrrikoii