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We develop a real-time, robust and accurate sign language recognition system leveraging deep convolutional neural networks(DCNN). Our framework is able to prevent common problems such as error accumulation of existing frameworks and it outperforms state-of-the-art frameworks in terms of accuracy, recognition time and usability.
Numerous approaches can be utilized for image enlargement, among them seam-carving, texture-synthesis, linear scaling and warping are commonly used. However, all of these methods have their disadvantages. In this paper, we propose a new image enlargement method inspired from seam-carving and texture synthesis, called Patch-Based Seam Synthesis. Our(More)
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