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Physical Sciences › Computer Science › Computer Vision and Pattern Recognition
Face mask detection using YOLOv3 and faster R-CNN models: COVID-19 environment
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Overview
Paper Summary
Conflicts of Interest
Identified Weaknesses
Rating Explanation
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Paper Summary
Paperzilla title
Mask or No Mask? YOLO and Faster R-CNN Face Off!
This paper compares YOLOv3 and Faster R-CNN for real-time face mask detection. Faster R-CNN had slightly better accuracy, while YOLOv3 significantly outperformed in speed, suggesting YOLOv3 is preferable for real-time applications like surveillance.
Possible Conflicts of Interest
None identified
Identified Weaknesses
Limited Dataset
The dataset used to train and evaluate the models is relatively small (~7500 images), which may limit the generalizability of the results to real-world scenarios with more diverse data.
Incomplete Evaluation
The authors compare YOLOv3 and Faster R-CNN based on inference time and average precision, but other important evaluation metrics like F1-score, recall, and area under the ROC curve are missing. A more comprehensive evaluation would be needed to draw stronger conclusions.
Limited Discussion of Limitations
The paper lacks a detailed discussion of the limitations of the proposed method. Addressing potential issues like variations in mask types, lighting conditions, and face orientations would strengthen the analysis.
Lack of Deployment Considerations
The paper's focus on real-time performance is valuable, but it does not adequately address the challenges of deploying the models on resource-constrained devices. A discussion of optimization techniques and model compression would be beneficial.
Rating Explanation
This paper presents a reasonably sound approach to face mask detection using well-established object detection models. However, the limited dataset size, incomplete evaluation metrics, and lack of in-depth discussion of limitations prevent it from receiving a higher rating. The study provides a solid foundation but requires further refinement to be considered a significant contribution.
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File Information
Original Title:
Face mask detection using YOLOv3 and faster R-CNN models: COVID-19 environment
File Name:
s11042-021-10711-8.pdf
[download]
File Size:
1.54 MB
Uploaded:
July 14, 2025 at 05:20 PM
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