Detection Confidence

Detection confidence, the reliability assigned to object detection predictions, is crucial for improving the robustness and accuracy of various computer vision systems. Current research focuses on enhancing confidence scores through methods like confidence boosting, incorporating shape and contextual information, and employing Bayesian approaches to refine probabilistic estimations. These advancements are improving the performance of object tracking, re-identification, and out-of-distribution detection in applications ranging from autonomous driving to medical image analysis, ultimately leading to more reliable and trustworthy AI systems.