基于深度学习的图像描述优化策略

doi:10.11896/jsjkx.230200091

Abstract

Abstract: Image captioning aims to describe image content with grammatically correct sentences and automatically generate text.Image captioning involves computer vision and natural language processing,which is a classic task in multimodal field.In recent years,a large number of studies have begun to focus on image captioning,a multimodal task that combines vision and language,and has achieved many breakthrough results.Most of the existing surveys on image captioning take technology as the core and analyze from the perspective of classification.Considering that image captioning based on deep learning has become the mainstream research method at present,and its essence is an image-to-sequence problem,this paper takes visual input subtasks and language output subtasks as the theme,takes optimization strategy as the core.The optimization logic and technical development trend of these two subtasks are compared and analyzed.The existing challenges and task variations of image captioning are discussed.Finally,the optimization strategy and development direction of image captioning based on deep learning are expected to be further clarified.

Key words: Image captioning, Deep learning, Computer vision, Natural language processing

CLC Number:

TP301

ZHOU Ziyi, XIONG Hailing. Image Captioning Optimization Strategy Based on Deep Learning[J].Computer Science, 2023, 50(8): 99-110.

References

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