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Two-Step CNN Framework for Text Line Recognition in Camera-Captured Images
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Outgoing claims: the papers this work cites, builds on, or argues with.
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AI Benchmark: Running Deep Neural Networks on Android Smartphones
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Mobile Phone Camera-Based Video Scanning of Paper Documents
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Accurate Scene Text Recognition Based on Recurrent Neural Network
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OCR as a Service: An Experimental Evaluation of Google Docs OCR, Tesseract, ABBYY FineReader, and Transym
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Segmentation of connected characters in text-based CAPTCHAs for intelligent character recognition
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Text recognition in document images obtained by a smartphone based on deep convolutional and recurrent neural network
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Text localization in camera captured images using fuzzy distance transform based adaptive stroke filter
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Efficient Object Detection Using Embedded Binarized Neural Networks
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A New Gradient Based Character Segmentation Method for Video Text Recognition
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inferredcites →https://doi.org/10.22204/2410-4639-2016-092-04-55-71openalex-snapshot
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inferredcites →https://doi.org/10.23919/date.2018.8342102openalex-snapshot
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inferredcites →https://doi.org/10.4230/lipics.itcs.2018.22openalex-snapshot
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inferredcites →https://doi.org/10.48550/arxiv.1406.2227openalex-snapshot
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Batch-normalized Maxout Network in Network
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