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we apply an improved deep convolutional neural network (CNN) in fruit category classification, which is a hotspot in computer vision field. We created an 8-layer deep convolutional neural network, and utilized parametric rectified linear unit to take the place of plain rectified linear unit, and placed dropout layer before each fully-connected layer. Data augmentation was used to help avoid overfitting. Our 8-layer deep convolutional neural network secured an overall accuracy of 95.67%. This proposed 8-layer method performs better than five state-of-the-art methods using traditional machine learning methods and one state-of the-art CNN method.



Algorithm Used:-

1. Convolution Neural Network

Course Curriculum

    • Fruit Classification Using Deep Learning Reference Paper 00:00:00
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