Abstract
Vision is one of the crucial senses and is the birthright of every human being. Its impairment or loss leads to various difficulties. Blind and Visually Impaired (BVI) people find it tough to maneuver outdoors daily. Even though the market is laden with countless aids for BVI people, there is still a lot to be achieved. The idea of every new research in the market is to assist these individuals in any possible way. Individuals deprived of vision require numerous reliable methods to overcome these barriers. Also, with the advent of science and technology, there is nothing that a human being can’t do. Researchers and manufacturers are coming up with new inventions and tech gadgets now and then. In this paper, Convolutional Neural Network (CNN) models, vgg16 and vgg19, are used along with the self-created dataset involving two classes: roads and crosswalks, which underwent the ML procedures resulting in the accurate detection of the respective classes.
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S Shrivastava, R., Singhal, A., Chandna, S. (2023). Towards Helping Visually Impaired People to Navigate Outdoor. In: Unhelkar, B., Pandey, H.M., Agrawal, A.P., Choudhary, A. (eds) Advances and Applications of Artificial Intelligence & Machine Learning. ICAAAIML 2022. Lecture Notes in Electrical Engineering, vol 1078. Springer, Singapore. https://doi.org/10.1007/978-981-99-5974-7_8
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