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A. Kundu
Researcher at State University of New York System
Publications - 11
Citations - 405
A. Kundu is an academic researcher from State University of New York System. The author has contributed to research in topics: Hidden Markov model & Word recognition. The author has an hindex of 8, co-authored 11 publications receiving 399 citations. Previous affiliations of A. Kundu include University at Buffalo & National Chiao Tung University.
Papers
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Journal ArticleDOI
Recognition of handwritten word: first and second order hidden Markov model based approach
A. Kundu,Yang He,Paramvir Bahl +2 more
TL;DR: In this work, handwritten word recognition problem is modeled in the framework of hidden Markov model (HMM), and Viterbi algorithm is used to recognize the sequence of letters consisting the word.
Proceedings ArticleDOI
Recognition of handwritten word: first and second order hidden Markov model based approach
A. Kundu,Yang He,Paramvir Bahl +2 more
TL;DR: The handwritten word recognition problem is modeled in the framework of the hidden Markov model (HMM) and the Viterbi algorithm is used to recognize the sequence of letters consisting the word.
Journal ArticleDOI
Robust edge detection
TL;DR: A new robust edge detection algorithm which performs equally well under a wide variety of noisy situations and a broad range of edges that is posed as a series of outlier detection problem.
Proceedings ArticleDOI
Off-line handwritten word recognition (HWR) using a single contextual hidden Markov model
TL;DR: A complete scheme for totally unconstrained handwritten word recognition based on a single contextual hidden Markov model (HMM) is proposed, which includes a morphology- and heuristics-based segmentation algorithm and a modified Viterbi algorithm that searches the globally best path based on the previous l best paths.
Proceedings ArticleDOI
Handwritten word recognition using HMM with adaptive length Viterbi algorithm
Ying He,M.-Y. Chen,A. Kundu +2 more
TL;DR: This work attempts to extend the earlier HMM scheme for naturally segmented word recognition to cursive and nonsegmented word Recognition, incorporated with an adaptive length Viterbi algorithm.