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@article{178160,
        author = {M.Saikiran and G.Venkata Subba Rao and M.Dheeraj Reddy and P.Akash Reddy and M.Vijay Kumar},
        title = {PNEUMONIA DETECTION USING DEEP LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {3244-3248},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178160},
        abstract = {Pneumonia is a life-threatening infectious disease that affects one or both of a person's lungs and is usually caused by the bacteria Streptococcus pneumoniae. According to the World Health Organization (WHO), one in three deaths in India is due to pneumonia. Chest X-rays used to diagnose pneumonia require experienced radiologists to evaluate. Thus, the development of an automatic pneumonia detection system would be useful for rapid treatment of the disease, especially in remote areas. Due to the success of deep learning algorithms for medical image analysis, convolutional neural networks (CNNs) have received much attention in disease classification. In addition, features learned on large datasets by pre- trained CNN models are very useful in image classification tasks. In this work, we try to create a pair of models that classify pneumonia and detect pneumonia based on lung X-rays.},
        keywords = {CNN, FLASK SERVER,IMAGE PROCESSING & PREDICTION,TENSERFLOW, XAMPP.},
        month = {May},
        }