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• W2891351915 abstract "Image captioning is one of the fundamental tasks in machine learning since the ability to generate text captions of an image can have a great impact by assisting us in day-to-day life. However, it is not just an object classification or recognition task, because the model must know the dependencies among the recognized objects and their attributes and encode that knowledge correctly in the caption using a natural language like English. Recently, the internet is overwhelmed with the huge amount of textual and visual data consisting of billions of unstructured images and videos. Meaningful captions will serve as useful keys for retrieval, creative searching, and powerful browsing of these images. In this paper, we present the goal of analysis and classification of the recent state-of-the-art in image captioning and discuss significant differences among them. We provide a comparative review of existing models, techniques with their advantages and disadvantages. Future directions in the field of automatic image caption generation are also explored." @default.
• W2891351915 created "2018-09-27" @default.
• W2891351915 creator A5046486752 @default.
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• W2891351915 date "2018-09-13" @default.
• W2891351915 modified "2023-09-26" @default.
• W2891351915 title "Captioning the Images: A Deep Analysis" @default.
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• W2891351915 doi "https://doi.org/10.1007/978-981-13-1513-8_100" @default.
• W2891351915 hasPublicationYear "2018" @default.
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