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@article{169083,
        author = {Vishal Pawar and Shubhankar Patil and Vedant Patil and Sarthiki Hegade},
        title = {Review On : AI-Powered Sensory Augmentation and  Visual Data Processing},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {475-479},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169083},
        abstract = {This review paper investigates the evolving landscape of machine learning techniques in the realm of computer vision, emphasizing their applicability to enhancing human sensory experiences. As artificial intelligence (AI) continues to advance, it presents unprecedented opportunities to improve human interaction with visual data. By analyzing various machine learning models and their methodologies, this paper highlights key techniques such as Contrastive Language-Image Pretraining (CLIP) and Bootstrapping Language-Image Pretraining (BLIP), which are integral to the development of AI-driven systems that augment sensory perception. These models facilitate real-time data processing, enabling efficient image categorization and accessibility solutions for visually impaired individuals. Furthermore, this review identifies future directions in the field, focusing on the integration of AI with real-time sensory inputs to create adaptive and inclusive technologies. The findings underscore the transformative potential of AI in bridging the gap between human perception and machine intelligence, paving the way for innovative applications that enhance everyday life and address diverse societal needs.},
        keywords = {Computer Vision, AI, ML, Image Processing, Classification, Visualization, Cross domain data integration, Speech to text, metadata.},
        month = {November},
        }