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@article{167489,
        author = {LEKHA NANKU PRAJAPATI and Girish S. Katkar and Ajay S. Ramteke},
        title = {Masked Face Recognition Technique for Different Type of Occlusion Area on Face},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {3},
        pages = {1411-1416},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=167489},
        abstract = {In response to the COVID-19 pandemic, wearing masks has become a common and necessary practice to prevent virus transmission. While effective for public health, masks obscure key facial features, complicating the task of facial recognition. Recognizing individuals wearing masks is particularly challenging due to the limited visibility of distinguishing facial characteristics. Recognizing and authenticating people wearing masks will be a long-established research area, and more efficient methods are needed for real-time MFR. This paper proposed methodology for masked face recognition using ResNet-50 model with MFR-2 dataset, aims to produce maximum accuracy. Pre-trained model ResNet-50 used MaxPooling layers to reduces the dimensionality of feature maps while retaining important information and ResNet-50 model Generated 0.82 accuracy for the identification of masked face. },
        keywords = {Convolutional Neural Networks (CNN), Corona virus disease 2019, Deep Learning, Masked face recognition.},
        month = {August},
        }