Style character generation method based on small number of samples and containing various normalization processing
A character generation and normalization technology, applied in neural learning methods, electrical digital data processing, natural language data processing, etc., can solve problems such as slow training speed
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[0064] Embodiment: A style character generation method based on a small number of samples and including multiple normalization processes, a style reference character data set is composed of several style characters, and a variety of standard font characters with the same content are used as character content prototype data sources , using an image translation model based on a deep generative adversarial network that includes a mixer and multiple normalization methods, and using the adversarial loss function proposed in this patent during training, an image translation model that includes multiple normalization methods for character style transfer can be trained. Unified character generation model; a fully trained model can use a small number or even one character with the same style as a style reference template to generate any character with the same writing or printing style, and the content of the generated character is determined by the input Content archetype with standard...
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