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• W2897584236 abstract "In this paper, we propose a modified strategy using sparse representation to identify the authorship of online handwritten documents. The note-worthy aspect of this paper lies in the introduction of a-priori information for each dictionary atom, that in a way indicates its degree of importance with respect to the dynamic characteristics of the writer. The methodology behind obtaining this information for the dictionary atoms is based on the computation of entropy values over histograms that are generated from the sparse coefficients during the training phase. The prelearned values are incorporated on the traditional schemes of “max” and “mean” pooling of sparse codes, thereby resulting in a modified writer descriptor. Experiments performed with the proposed sparse classification strategy on the handwritten samples of the IAM and IBM-UB1 online handwriting databases demonstrate promising results." @default.
• W2897584236 created "2018-10-26" @default.
• W2897584236 creator A5031728230 @default.
• W2897584236 creator A5081411825 @default.
• W2897584236 date "2021-01-01" @default.
• W2897584236 modified "2023-10-16" @default.
• W2897584236 title "Modified Sparse Representation Classification Framework for Online Writer Identification" @default.
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• W2897584236 doi "https://doi.org/10.1109/tsmc.2018.2871267" @default.
• W2897584236 hasPublicationYear "2021" @default.
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