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A System for Offline Cursive Handwritten Word - DSpace MIT - dspace mit

A System for Offline Cursive Handwritten Word - DSpace MIT - dspace mit 2025

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The document presents a thesis by Marlon Abayan on a system for offline cursive handwritten word recognition, introducing a novel approach called Hidden Markov Model with Multiple Observation Sequences (HMMMOS). The thesis details the challenges of recognizing cursive handwriting due to variations and overlaps in characters. It describes the architecture of the recognition system, which includes preprocessing, feature extraction, and neural network classifiers. The work evaluates different neural network models and implements a dynamic programming algorithm for word recognition. Additionally, it discusses improvements through verification and correction using lexicon context, as well as parallel implementations to enhance performance.

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