Sentence examples for cnn model from inspiring English sources
Bilinear CNN model (B-CNN) [8] extract features from non-linearity activations of convolutional layers from two CNN, achieving remarkable performance in fine-grained visual recognition without any bounding-box or part annotation.
Analysis on deeply learned features: Owing to the recent breakthrough in deep learning techniques, particularly deep convolutional neural networks (CNNs), we have made comparisons against a recent work that used object features extracted from a pre-trained CNN model [35].
Fig. 2 CNN model structure.
CNN model from mastic could better distinguished different compaction methods while CNN model from aggregates could recognize different gradation types better.
Suppose that there are N feature maps from a certain convolutional layer of the CNN model.
The trained CNN model achieved 93% classification accuracy on the test set.
The description is of feature extraction in text categorization of several typical application of CNN model.
If we train a CNN model with insufficient training samples, it would lead to overfitting.
The parameters, training and analysis of this CNN model were introduced in our previous work [5].
Thus we introduce a 1-layer CNN model as a comparison.
