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@article{165389,
        author = {Nagam Venkata Sai Sri Shanmukhi and G.Jyoshna},
        title = {Blind Assistance In Object Detection And Generating Voice Alerts},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {11},
        number = {1},
        pages = {931-934},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=165389},
        abstract = {Visually impaired individuals encounter numerous challenges when navigating unfamiliar urban environments. One of the most significant obstacles they face is identifying obstacles while moving. It's widely known that there are approximately 285 million visually impaired individuals worldwide, roughly equivalent to 20% of the population of India. Navigating independently poses regular and ongoing challenges for them. To address this, we developed an Integrated Machine Learning System. This system empowers visually impaired individuals to recognize and categorize common everyday objects in real-time, providing voice feedback and distance calculations to warn them of proximity to obstacles. Our project is centered on providing visual assistance to the visually impaired, utilizing an Android smartphone equipped with a camera to identify surroundings and deliver audio output. By leveraging the user's auditory sense, we aim to compensate for their visual impairment.},
        keywords = {Object Detection, Tensor flow object detection, Surroundings, Distance Calculations, Auditory Sense, Real-time.},
        month = {},
        }