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- W4285199478 abstract "Image captioning refers to generating a description for an image. Remote sensing image(RSI) captioning is a cross-field between RSI processing and natural language processing. Most of the RSI suffer from large inter-class similarity. The proposed system uses visual question answering (VQA) to overcome this problem and to aid the caption generation process. VQA model helps the system to identify important words that can be included in the captions. By doing this, the captions include all the objects in the image and the count of those objects, thus making the captions more informative. The process has two phases. The first phase performs VQA using three levels of attention. The model uses the knowledge that it has obtained from the VQA to enhance the captions in the second phase. An overall BLEU score of 78.8% is obtained by the proposed model." @default.
- W4285199478 created "2022-07-14" @default.
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- W4285199478 date "2022-01-01" @default.
- W4285199478 modified "2023-09-28" @default.
- W4285199478 title "Remote Sensing Image Captioning via Multilevel Attention-Based Visual Question Answering" @default.
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- W4285199478 doi "https://doi.org/10.1007/978-981-19-0475-2_41" @default.
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