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@article{159197,
        author = {Harsh Ghosalkar and Jatin Singh and Durvesh Thombare and Rishabh Gilda and Preeti Satao},
        title = {Crack And Pothole Detection using YOLO},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {11},
        pages = {666-669},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=159197},
        abstract = {Because of ecological changes and low quality of development materials, breaks might foster in the walls of the structure or potholes might foster out of roads causing heavy damage to the infrastructure. One of the underlying indications of the corruption of a substantial surface or a material is cracks. Manual review of cracks and potholes has numerous downsides since it’s tedious and it totally relies on expert's information and experience. For the crack and pothole detection and analysis the following model uses Convolutional Neural Network (CNN) in substitution for manual approach. The You Only Look Once (YOLO) algorithm overcomes the drawbacks of manual inspection and other image processing techniques. The algorithm is projected to give real time detection of potholes which will help authorities to identify the damage and fix it before the condition worsens.},
        keywords = {CNN, YOLO.},
        month = {},
        }