mlsanityData to 7 Oct 2026

Face Mask Detection using Transfer Learning of InceptionV3

arXiv 2009.08369 ↗First posted 17 Sep 2020cs.CV eess.IVcited by 23

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Abstract (arXiv)

The world is facing a huge health crisis due to the rapid transmission of coronavirus (COVID-19). Several guidelines were issued by the World Health Organization (WHO) for protection against the spread of coronavirus. According to WHO, the most effective preventive measure against COVID-19 is wearing a mask in public places and crowded areas. It is very difficult to monitor people manually in these areas. In this paper, a transfer learning model is proposed to automate the process of identifying the people who are not wearing mask. The proposed model is built by fine-tuning the pre-trained state-of-the-art deep learning model, InceptionV3. The proposed model is trained and tested on the Simulated Masked Face Dataset (SMFD). Image augmentation technique is adopted to address the limited availability of data for better training and testing of the model. The model outperformed the other recently proposed approaches by achieving an accuracy of 99.9% during training and 100% during testing.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Sep 2020.

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Citing papers per year: 2021: 8; 2022: 5; 2023: 6; 2024: 3; 2025: 1.

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  1. 2021Modality specific U-Net variants for biomedical image segmentation: A surveycited by 20
  2. 2024Detection of a facemask in real-time using deep learning methods: Prevention of Covid 19cited by 11
  3. 2022Periocular Biometrics and its Relevance to Partially Masked Faces: A Surveycited by 9
  4. 2021WearMask: Fast In-browser Face Mask Detection with Serverless Edge Computing for COVID-19cited by 5
  5. 2021Unconstrained Face-Mask & Face-Hand Datasets: Building a Computer Vision System to Help Prevent the Transmission of COVID-19cited by 5
  6. 2021CPPE-5: Medical Personal Protective Equipment Datasetcited by 5
  7. 2022A Survey on Masked Facial Detection Methods and Datasets for Fighting Against COVID-19cited by 5
  8. 2025Rethinking Membership Inference Attacks Against Transfer Learningcited by 5
  9. 2021Mask or Non-Mask? Robust Face Mask Detector via Triplet-Consistency Representation Learningcited by 3
  10. 2021A Deep Learning-based Approach for Real-time Facemask Detectioncited by 2
  11. 2021Class dependency based learning using Bi-LSTM coupled with the transfer learning of VGG16 for the diagnosis of Tuberculosis from chest x-rayscited by 1
  12. 2022Mask Usage Recognition using Vision Transformer with Transfer Learning and Data Augmentationcited by 1
11 more
  1. 2022Adversarial Learning-based Stance Classifier for COVID-19-related Health Policiescited by 1
  2. 2023A transfer learning approach with convolutional neural network for Face Mask Detectioncited by 1
  3. 2023ARTEMIS: Using GANs with Multiple Discriminators to Generate Artcited by 1
  4. 2024A Comprehensive Survey of Masked Faces: Recognition, Detection, and Unmaskingcited by 1
  5. 2024A Review and Implementation of Object Detection Models and Optimizations for Real-time Medical Mask Detection during the COVID-19 Pandemiccited by 1
  6. 2021A Comparative Analysis of Machine Learning Approaches for Automated Face Mask Detection During COVID-19cited by 0
  7. 2022Real-Time Mask Detection Based on SSD-MobileNetV2cited by 0
  8. 2023A Benchmark Study by using various Machine Learning Models for Predicting Covid-19 trendscited by 0
  9. 2023Wearing face mask detection using deep learning through COVID-19 pandemiccited by 0
  10. 2023Automated Speaker Independent Visual Speech Recognition: A Comprehensive Surveycited by 0
  11. 2023Grassroots Operator Search for Model Edge Adaptationcited by 0