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@article{162529,
        author = {Navyasri Gangapuram and Hemanth Mittapally and G.Kadirvelu},
        title = {Image Caption Generator },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {10},
        pages = {410-413},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=162529},
        abstract = {In the era of digital imagery and social media, the demand for engaging image captions has grown exponentially. This research project explores the fusion of artificial intelligence and natural language processing techniques to automatically generate captivating and contextually relevant captions for images. We present a novel approach that leverages deep learning models and large-scale image-text datasets to train a caption generation system. Our methodology involves pre-training a neural network on a diverse corpus of text data and fine-tuning it on a curated dataset of images and corresponding captions. We evaluate the system's performance using both quantitative metrics, such as BLEU and METEOR, and qualitative assessments by human judges. 
The results demonstrate the effectiveness of our approach in generating captions that not only accurately describe the content of the images but also engage and resonate with human audiences. We discuss the implications of this research for content creators, marketers, and social media platforms, highlighting the potential for enhancing user experiences and automating caption generation at scale. This work represents a significant step towards harnessing AI-driven creativity in the realm of visual content and text generation, with promising applications in social media marketing, content recommendation systems, and accessibility for visually impaired user},
        keywords = {},
        month = {},
        }