DeepGD: A Multi-Objective Black-Box Test Selection Approach for Deep Neural Networks

arXiv:2303.04878v5 Announce Type: replace
Abstract: Deep neural networks (DNNs) are widely used in various application domains such as image processing, speech recognition, and natural language processing. However, testing DNN models may be challenging due to the complexity and size of their input domain. Particularly, testing DNN models often requires generating or exploring large unlabeled datasets. In practice, DNN test oracles, which identify the correct outputs for inputs, often require expensive manual effort to label test data, possibly involving multiple experts …

abstract and natural language processing application arxiv box complexity cs.lg cs.pf cs.se dnn domain domains image image processing language language processing multi-objective natural natural language natural language processing networks neural networks processing recognition speech speech recognition test testing type