Model significantly outperforms the previous methods. On synthesized samples with simulated random disturbance, our FCN model As a deep neural architecture, FCN canĪutomatically learn useful features from raw text line images. The necessary context around a horizontal position to determinate whether this ![]() ![]() Given a wide enough receptive field, FCN can utilize Successful architecture called fully convolutional networks (FCN) in the field Reframing it as a semantic segmentation problem. In this work, we particularly tackle the Chinese/English mixed case by Mainly focus on monolingual texts and are not suitable for multilingual-lingualĬases. OCR character segmentation for multilingual printed documents is difficultĭue to the diversity of different linguistic characters. Chinese/English mixed Character Segmentation as Semantic Segmentation
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