Character and handwritten text recognition are crucial tasks in Natural Language Processing (NLP), with applications ranging from document analysis to data entry automation. Transfer learning has emerged as a powerful approach to enhance recognition performance by leveraging pre-trained models and knowledge from related tasks.
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Character and handwritten text recognition are crucial tasks in Natural Language Processing (NLP), with applications ranging from document analysis to data entry automation. Transfer learning has emerged as a powerful approach to enhance recognition performance by leveraging pre-trained models and knowledge from related tasks.
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Bheema-Shanker-Neyigapula/Transfer-Learning-in-TensorFlow-for-Advancing-Character-and-Handwritten-Text-Recognition
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Character and handwritten text recognition are crucial tasks in Natural Language Processing (NLP), with applications ranging from document analysis to data entry automation. Transfer learning has emerged as a powerful approach to enhance recognition performance by leveraging pre-trained models and knowledge from related tasks.
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