Semi-supervised-transfer-learning character recognition method and system based on convolutional neural network
A convolutional neural network and transfer learning technology, applied in neural learning methods, character recognition, character and pattern recognition, etc., can solve the problems of affecting recognition accuracy, difficult to obey statistical distribution, and low sample adaptability, and achieve high recognition accuracy. , the effect of improving adaptability
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[0045] The specific embodiments of the present invention will be described in further detail below in conjunction with the drawings and embodiments. The following examples are used to illustrate the present invention, but not to limit the scope of the present invention.
[0046] figure 1 It is a flowchart of a semi-supervised transfer learning character recognition method based on convolutional neural network provided by an embodiment of the present invention, such as figure 1 As shown, the method includes:
[0047] Step 1. Input the batch of character image samples without category labels in the target domain as a test sample set into the convolutional neural network after semi-supervised transfer learning, and identify the character images of the test sample set;
[0048] The convolutional neural network after the semi-supervised transfer learning consists of batch character image samples with category labels in the source domain, batch character image samples with category labels ...
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