图像字幕技术的比较分析

Diya Theresa Sunil, Seema Safar, Abhijit Das, Amijith M M, Devika M Joshy
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引用次数: 0

摘要

图像字幕是生成准确表示图像内容的文本描述的任务。这项任务需要将物体识别和场景理解等计算机视觉技术与自然语言处理相结合,以产生类似人类的图像描述。随着时间的推移,已经引入了各种模型来执行图像字幕,所有这些模型都旨在准确地描述图像的内容。这些模型具有实际应用,例如改善多媒体内容的可访问性、帮助有视觉障碍的个人、医学图像字幕以及增强图像搜索和检索。本文对其中的一些模型进行了探讨,并使用不同的评价指标对其有效性进行了研究。
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A Comparative Analysis of Image Captioning Techniques
Image captioning is the task of generating a textual description that accurately represents the content of an image. This task involves combining computer vision techniques, such as object recognition and scene understanding, with natural language processing to produce a human-like description of an image. Over time, various models have been introduced to perform image captioning, all aiming to accurately describe the content of an image. These models have practical applications such as improving the accessibility of multimedia content, assisting individuals with visual impairments, medical image captioning, and enhancing image search and retrieval. This paper explores some of the models and studies their efficiency using different evaluation metrics.
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