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@article{157920,
        author = {Noor Fathima and Lakshmi M R and S.Tharunram and Owais Khan Hannan and Vibha S},
        title = {X-Ray Examination Using Deep Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {8},
        pages = {265-270},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=157920},
        abstract = {In a human body bone is one of the most important part. Bones support your body and allow you to move. They protect your brain, heart, and other organs from injury. Bone is a living, growing tissue[11]. Many times due to accidents the bone can be broken. The X-Ray Examination helps detecting whether the bone was broken or not. The X-Ray Examiner helps detecting the fracture more accurately. The modelling of this software is done by using deep learning and trained datasets available at  GRAZPEDWRI-DX. The GRAZPEDWRI-DX is an open [3] dataset containing 20327 annotated pediatric trauma wrist radiograph images of 6091 patients. The aim is to differentiate between a broken bone and a healthy bone. We will be using trained datasets and YoloV7 model, In order to expand the amount of the data set, data augmentation techniques that have been deployed.},
        keywords = {Deep Learning, YoloV7, Machine Learning.},
        month = {},
        }