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Face Detection Dataset is now a pillar of contemporary computer vision, driving applications in security, biometrics, social media, and beyond. But developing a high-performance face detection model isn't merely a matter of selecting the optimal algorithm u2014 the dataset matters. Perhaps the most significant challenge in face detection is handling noisy data u2014 mislabeled samples, low-quality images, and inconsistent annotations that can undermine model performance. In this blog, weu2019ll explore how noisy data impacts face detection models and the most effective techniques and tools for handling it

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