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Automatic Bangla Image Captioning Based on Transformer Model in Deep Learning

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dc.contributor.author Hossain, Md. Anwar
dc.contributor.author Hasan, Mirza AFM Rashidul
dc.contributor.author Hossen, Ebrahim
dc.contributor.author Asraful, Md
dc.contributor.author Faruk, Md. Omar
dc.contributor.author Abadin, AFM Zainul
dc.contributor.author Ali, Md. Suhag
dc.date.accessioned 2024-04-28T10:10:52Z
dc.date.available 2024-04-28T10:10:52Z
dc.date.issued 2023-11-02
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/12197
dc.description.abstract "Indeed, Image Captioning has become a crucial aspect of contemporary artificial intelligence because it has tackled two crucial parts of the AI field: Computer Vision and Natural Language Processing. Currently, Bangla stands as the seventh most widely spoken language globally. Due to this, image captioning has gained recognition for its significant research accomplishments. Many established datasets are found in English but no standard datasets in Bangla. For our research, we have used the BAN-Cap dataset which contains 8091 images with 40455 sentences. Many effective encoder-decoder and Visual Attention approaches are used for image captioning where CNN is utilized for the encoder and RNN is used for the decoder. However, we suggested a transformer-based image captioning model in this study with different pre-train image feature extraction models like Resnet50, InceptionV3, and VGG16 using the BAN-Cap dataset and find out its effective efficiency and accuracy based on many performances measured methods like BLEU, METEOR, ROUGE, CIDEr and also find out the drawbacks of others model. " en_US
dc.language.iso en_US en_US
dc.publisher Institute of Advanced Engineering and Science (IAES) en_US
dc.subject Image processing en_US
dc.subject Natural language en_US
dc.subject Language processing en_US
dc.title Automatic Bangla Image Captioning Based on Transformer Model in Deep Learning en_US
dc.type Article en_US


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