main webpage W Topic Convolutional Neural Network International Journal of Advanced Computer Science and Applications • Vol 13 • No 11 Constraints on Hyper-parameters in Deep Learning Convolutional Neural Networks 2022 Convolutional Neural Network (CNN), a type of Deep Learning, has a very large number of hyper-meters in contrast to the Artificial Neural Network (ANN) which makes the task of CNN training more demanding. The reason why the task of tuning parameters optimizat… Article Open Convolutional Neural Network Open Article Page

Convolutional Neural Network

Artificial neural network Convolutional neural network ( CNN ) is a regularized type of feed- forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections. For example, for each neuron in the fully-connected layer 10,000 weights would be required for processing an image sized 100 × 100 pixels. However, applying cascaded convolution (or cross-correlation) kernels, only 25 neurons are required to process 5x5-sized tiles. Higher-layer features are extracted from wider context windows, compared to lower-layer features. Critical Symbolic Virtual Narrative Open Convolutional Neural Network Open Article Page

Exploring foci of: International Journal of Advanced Computer Science and Applications • Vol 13 • No 11 Constraints on Hyper-parameters in Deep Learning Convolutional Neural Networks 2022 Convolutional Neural Network (CNN), a type of Deep Learning, has a very large number of hyper-meters in contrast to the Artificial Neural Network (ANN) which makes the task of CNN training more demanding. The reason why the task of tuning parameters optimization is difficult in the CNN is the existence of a huge optimization space comprising a large number of hyper-parameters such as the number of layers, number of neurons, number of kernels, stride, padding, rows or columns truncation, parameters of the backpropa… Open Article Page

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Explore Convolutional Neural Network W Topic Convolutional Neural Network International Journal of Advanced Computer Science and Applications • Vol 13 • No 11 Constraints on Hyper-parameters in Deep Learning Convolutional Neural Networks 2022 Convolutional Neural Network (CNN), a type of Deep Learning, has a very large number of hyper-meters in contrast to the Artificial Neural Network (ANN) which makes the task of CNN training more demanding. The reason why the task of tuning parameters optimizat… Article Critical Symbolic Virtual Narrative Open Convolutional Neural Network Open Article Page