Computer Vision and Multimodal AI

Vision models fail in ways tabular models never do. Shortcut learning and background bias, preprocessing mistakes that silently destroy accuracy, occlusion, motion blur and low light, small-object detection, and the interpretability tools that show which pixels a model actually used.