• Rahul Dahiya
• Dr. Rahul Rishi

Image captioning, an area that has combined computer vision and natural language processing, has advanced significantly in three key domains: real-world, medical, and captioning for the visually impaired. In real-world applications, foundational deep learning models like CNNs and RNNs evolved with attention mechanisms, reinforcement learning, and bidirectional LSTMs to enhance contextual accuracy and language fluency. In medical environments, captioning involves the interpretation of biomedical images using contextualized representations and multimodal techniques that help in automated diagnosis and clinical workflows. For visually impaired users, systems focus on accessibility, tackling real-world challenges, text comprehension that involves datasets like TextCaps, and enhancing multimodal inclusivity so that it expresses visual and textual content in scenes. The problem areas still persist, including handling imbalanced datasets, improving context understanding, and usability in special-purpose settings. The future areas of opportunity are refinements in domain-specific models, emergent techniques, such as transformer architectures, and improved accessibility for a wide spectrum of applications. By filling these gaps, image captioning can then further bridge visual data with actionable insights to all lines of applications from healthcare to assistive technologies while guiding future researchers towards developing more robust, inclusive, and context-aware systems.

Image Captioning, Computer Vision and Natural Language Processing (CV-NLP Integration), Attention Mechanisms,, Multimodal Fusion (Visual-Textual-Audio), Contextual Understanding (Graph Neural Networks, Transformers)

"Review of AI Image Captioning: A Multimodal Perspective Towards Healthcare, Accessibility, And Inclusive Applications", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 11, page no.g46-g55, November-2025, Available :http://www.jetir.org/papers/JETIR2511649.pdf

"Review of AI Image Captioning: A Multimodal Perspective Towards Healthcare, Accessibility, And Inclusive Applications", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 11, page no. ppg46-g55, November-2025, Available at : http://www.jetir.org/papers/JETIR2511649.pdf