neural_network.convolution_neural_network¶
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Name - - CNN - Convolution Neural Network For Photo Recognizing Goal - - Recognize Handwriting Word Photo Detail: Total 5 layers neural network
Convolution layer
Pooling layer
Input layer layer of BP
Hidden layer of BP
Output layer of BP
Author: Stephen Lee Github: 245885195@qq.com Date: 2017.9.20 - - - - - – - - - - - - - - - - - - - - - - - - - - - -
Classes¶
Module Contents¶
- class neural_network.convolution_neural_network.CNN(conv1_get, size_p1, bp_num1, bp_num2, bp_num3, rate_w=0.2, rate_t=0.2)¶
- _calculate_gradient_from_pool(out_map, pd_pool, num_map, size_map, size_pooling)¶
calculate the gradient from the data slice of pool layer pd_pool: list of matrix out_map: the shape of data slice(size_map*size_map) return: pd_all: list of matrix, [num, size_map, size_map]
- _expand(data)¶
- _expand_mat(data_mat)¶
- convolute(data, convs, w_convs, thre_convs, conv_step)¶
- convolution(data)¶
- do_round(x)¶
- pooling(featuremaps, size_pooling, pooling_type='average_pool')¶
- predict(datas_test)¶
- classmethod read_model(model_path)¶
- save_model(save_path)¶
- sig(x)¶
- train(patterns, datas_train, datas_teach, n_repeat, error_accuracy, draw_e=bool)¶
- conv1¶
- num_bp1¶
- num_bp2¶
- num_bp3¶
- rate_thre = 0.2¶
- rate_weight = 0.2¶
- size_pooling1¶
- step_conv1¶
- thre_bp2¶
- thre_bp3¶
- thre_conv1¶
- vji¶
- w_conv1¶
- wkj¶