Sample Probing

Sample Probing is a technique used in the field of computer vision to evaluate and optimize model performance. It involves systematically selecting samples for testing with the aim of identifying weaknesses and biases in the model on specific datasets, thereby enhancing the model's generalization and robustness. Its application value lies in the ability to diagnose model issues in detail, guiding model training and parameter tuning, ensuring the stability and accuracy of the model in practical applications.