Abstract: The Image Caption Generator utilizes cutting-edge deep learning techniques to transform the way machines interact with visual content. By leveraging state-of-the-art Convolutional Neural Networks (CNNs), it extracts detailed features from images, enabling the generation of coherent and contextually appropriate captions. This is further enhanced by advanced language models such as Transformer-based architectures, ensuring accurate linguistic alignment. The project's impact is profound and diverse. It introduces a higher level of accessibility for individuals with visual impairments by providing verbal descriptions of images, empowering them to independently engage with visual content. Additionally, it simplifies content creation, benefiting social media influencers and content creators by automatically adding descriptive captions, saving time and effort. Users across various platforms benefit from enriched interactions as they enhance their posts with meaningful image captions, thereby increasing engagement and communication. Moreover, the Image Caption Generator improves image search and retrieval, enabling users to quickly locate relevant images. Its applications extend to content moderation and educational support, underscoring its versatile utility. With the potential for multilingual support and contributions to assistive technologies, the Image Caption Generator represents a significant advancement in artificial intelligence. By amalgamating images and language, it heralds a future of improved human-computer interaction, establishing a precedent for visual comprehension in the digital age.
Keywords: Image Caption Generator, Deep learning techniques, Convolutional Neural Networks (CNNs).
Cite:
Sharath Kumar, Pavan H R, Prashith C Hegde, Srajan S Shetty , Suhas S Shetty, "DeepVision Captioneer : Image Caption Generator For Visually Impaired ", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 3, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.133106.
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DOI:
10.17148/IJARCCE.2024.133106
