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Reading Text in Natural Scene Images via Deep Neural Networks

机译:通过深度神经网络读取自然场景图像中的文本

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摘要

Text recognition in the natural scenes have gained much attention in recent years. Although optical character recognition (OCR) was well studied in the past, many effects including different backgrounds, font styles, illumination and noises make it a challenge problem. In this paper, we propose a novel method based on the deep neural networks to recognize characters and words in the natural scene images. We use a convolutional neural network (CNN) model based on the VGG-Net, emphasizing more information on the network architecture. We conducted experiments on the state-of-art benchmark datasets in the literature, and demonstrated the effectiveness of our method.
机译:近年来,自然场景中的文本识别备受关注。尽管过去已经对光学字符识别(OCR)进行了深入研究,但是包括不同背景,字体样式,照明和噪音在内的许多效果使它成为一个难题。在本文中,我们提出了一种基于深度神经网络的新方法来识别自然场景图像中的字符和单词。我们使用基于VGG-Net的卷积神经网络(CNN)模型,着重介绍有关网络体系结构的更多信息。我们对文献中最新的基准数据集进行了实验,并证明了我们方法的有效性。

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