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@article{155127,
        author = {G.Shanmukhi Rama},
        title = {Chest X-ray image-based Covid-19 Detection using Deep Learning Algorithm },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {12},
        pages = {1415-1422},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155127},
        abstract = {The entire world is dealing with the Coronavirus, which has shattered our lives in innumerable ways. The number of people affected due to the virus is increasing at a pace that has been never witnessed before, leading to a rise in the need for medical facilities and equipment. In the digital revolution we exist in, every field of life is majorly reliant on technology for every daily need of life. Our study focused on developing a deep learning model for the detection of Coronavirus from chest X-ray images.
 To detect Covid-19 data pre-processing would be performed on the raw data of X-ray images. This is the first and the most crucial step as it prepares the data by avoiding the noise and missing values by converting it into a usable format that can directly be used for machine learning models. As the performance of deep learning neural networks often improves with the amount of data available, data augmentation techniques are used to artificially create new training data from existing training data. 
Machine learning and Computer Vision techniques are further being implemented for other various operations. One hot encoding is performed as it allows the representation of categorical data to be more expressive since most machine learning algorithms cannot work with categorical data directly. VGG 16, a convolutional neural network architecture, efficient image classification, and localization mechanisms are applied. The accuracy and loss curves are plotted using the metaplot libraries to better the efficient visualization of the model.},
        keywords = { Covid-19, Convolutional Neural Network, Computer Vision, Chest X-ray images, Machine learning },
        month = {},
        }