DNN Testing

Deep Neural Network (DNN) testing is aimed at evaluating and verifying the reliability and robustness of DNN models. It involves systematically detecting the model's behavior under various inputs to ensure stable and accurate performance in real-world applications. This task not only focuses on the predictive performance of the model but also emphasizes the identification and correction of potential errors and anomalies, thereby enhancing the safety and credibility of the model. In the context of increasing threats such as adversarial attacks, DNN testing has become a critical component in ensuring model quality.