AI vision robustness diagram: SeoulTech tests models with noise and corruptions

SeoulTech Develops a Framework to Shield AI Vision

SeoulTech, the Seoul National University of Science and Technology, developed a framework to expose the blind spots of AI vision systems against noise, corruptions, and adversarial attacks. The tool measures how much a model’s accuracy drops when the input image is minimally altered, then uses those results to retrain it. It’s part of a broader trend: demanding robustness testing before deploying AI vision in critical environments.