辅助视觉图像标题机器人

Prof.Anandkumar Birajdar
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引用次数: 0

摘要

自动生成图像含义的简短描述具有挑战性,因为图像在不同语言中可能具有不同的内涵。然而,由于一张图片包含了大量信息,要解析出必要的上下文并用它来造句是一项挑战。对于视障人士来说,这是一种独立行走的好方法。这类系统可以利用新兴的深度学习编程技术来构建。本文介绍了图像字幕机器人的开发过程,旨在帮助视障人士。我们在 MSCOCO 数据集上使用 Transformer 编码器和 Inception v3 进行图像处理建模,从而提高了字幕生成的准确性。图像标题需要为图像生成文字说明,这是我们研究的主要重点。我们通过在训练过程中使用 Transformer 编码器来提高标题生成的准确性。该模型的结果被翻译成语音,以造福视障人士。关键词:CNN、谷歌文本到语音、MS-COCO、Inspection v3。
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Image Caption Bot for Assistive Vision
It's challenging to automatically produce brief descriptions of an image's meaning because it can have diverse connotations in different languages. However, due to the vast amount of information packed into a single image, it is challenging to parse out the necessary context to use it to build sentences. It's a great way for the visually impaired to get around independently. This type of system can be built using the emerging programming technique of deep learning. This paper presents the development of an Image Caption Bot designed to aid individuals with visual impairments. We achieve enhanced accuracy in caption generation by modeling on the MSCOCO dataset using a Transformer encoder and Inception v3 for image processing. Image captioning, which entails generating textual descriptions for images, is the primary focus of our research. We achieve enhanced accuracy in caption generation by utilizing a Transformer encoder during training. The MSCOCO dataset serves as a valuable The results of the model are translated into speech for the benefit of the visually handicapped. Keywords—CNN, Google Text To Speech, MS-COCO, Inspection v3.
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