Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bangla Image Caption Generation through CNN-Transformer based
  Encoder-Decoder Network   Automatic Image Captioning is the never-ending effort of creating
syntactically and validating the accuracy of textual descriptions of an image
in natural language with context. The encoder-decoder structure used throughout
existing Bengali Image Captioning (BIC) research utilized abstract image
feature vectors as the encoder's input. We propose a novel transformer-based
architecture with an attention mechanism with a pre-trained ResNet-101 model
image encoder for feature extraction from images. Experiments demonstrate that
the language decoder in our technique captures fine-grained information in the
caption and, then paired with image features, produces accurate and diverse
captions on the BanglaLekhaImageCaptions dataset. Our approach outperforms all
existing Bengali Image Captioning work and sets a new benchmark by scoring
0.694 on BLEU-1, 0.630 on BLEU-2, 0.582 on BLEU-3, and 0.337 on METEOR.

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The categories of this paper are: plasm-ph
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The categories of this paper are: physics
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The categories of this paper are: hep-ph
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The categories of this paper are: hep-th
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The categories of this paper are: patt-sol
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The categories of this paper are: hep-lat
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The categories of this paper are: q-fin
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The categories of this paper are: nlin
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The categories of this paper are: nucl-ex
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The categories of this paper are: nucl-th
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The categories of this paper are: cond-mat
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The categories of this paper are: eess
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The categories of this paper are: mtrl-th
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The categories of this paper are: chem-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: econ