LEVERAGING DEEP LEARNING TOOLS AND TECHNIQUES TO DETECT AND RECOGNISE OPTICAL CHARACTER
Rishit Garkhel
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Abstract
The issue of the picture to message-based transformation continues in numerous spaces of use. This task tries to arrange an individual manually written person to interpret transcribed text into an advanced structure. To perform this research, we will use two main approaches: matching numbers and segmentation of characters. For the prior approach, we will use CNN with different structures for model training that will classify characters with high precision. For the later process, we will implement LSTM for each character bounding box.
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