Pneumonia is an inflammatory lung disease which mainly affects the small air sacs known as alveoli. Symptoms of Pneumonia usually involves a mixture of painful or dry cough, chest discomfort, fatigue and difficulties in breathing. So, symptoms of pneumonia can be detected using chest x-rays. Since chest x-rays plays an important role in the detection of pneumonia a deep learning approach can be used for the detection in order to automate it. In this paper the implementation of deep learning approach for the chest x-rays is proposed. This approach has three convolution layers each with 32 neurons with three different channels (3*3). In order to obtain a more robust accuracy, images are transformed based on various parameters. Experimental analysis validates the accuracy of proposed model as 88.68%. The training accuracy and validation accuracy of the model in each epoch is analysed and observed as comparatively high than conventional process.


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    Titel :

    Deep Learning Approach to detect Pneumonia


    Beteiligte:
    Gawali, Abhishek (Autor:in) / Bide, Pramod (Autor:in) / Kate, Vaibhavi (Autor:in) / Kothastane, Chaitali (Autor:in) / Hirani, Ebrahim (Autor:in)


    Erscheinungsdatum :

    05.11.2020


    Format / Umfang :

    287863 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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