Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Handwritten Devanagari Script Segmentation: A non-linear Fuzzy Approach   The paper concentrates on improvement of segmentation accuracy by addressing
some of the key challenges of handwritten Devanagari word image segmentation
technique. In the present work, we have developed a new feature based approach
for identification of Matra pixels from a word image, design of a non-linear
fuzzy membership functions for headline estimation and finally design of a
non-linear fuzzy functions for identifying segmentation points on the Matra.
The segmentation accuracy achieved by the current technique is 94.8%. This
shows an improvement of performance by 1.8% over the previous technique [1] on
a 300-word dataset, used for the current experiment.

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The categories of this paper are: nlin
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The categories of this paper are: gr-qc
3
The categories of this paper are: physics
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The categories of this paper are: math
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The categories of this paper are: nucl-th
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The categories of this paper are: acc-phys
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The categories of this paper are: dg-ga
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The categories of this paper are: chao-dyn
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The categories of this paper are: econ
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The categories of this paper are: eess
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The categories of this paper are: q-alg
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The categories of this paper are: hep-ex
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The categories of this paper are: hep-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: plasm-ph
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The categories of this paper are: cond-mat