R Tutorial 31: Convolutional Neural Network (CNN) in R using Keras from Python for Image Recognition
This video is going to show how to construct Convolutional Neural Network (CNN) in R using Keras from Python for image recognition. Parameters to adjust are (1) filter size, (2) number of filters, (3) stride, (4) activation function, (5) padding, (6) loss function, (7) optimizer, (8) metrics for model performance, (9) pooling method, (10) drop out rate, (11) validation size, and some other adjustment for model. Methods used in this example are (1) Rectified Linear Unit (ReLU), (2) Stochastic Gradient Descent, (3) Binary Cross Entropy, (4) Max Pooling, (5) Fully Connected Neural Network. Please refer to Keras and research papers for more information and adjustment for Convolutional Neural Network.
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