This is the first version of the codes for our outcoming paper: Correlations Between Deep Neural Network Model Coverage Criteria and Model Qualit
Deep Neural Networks (DNN) are typically tested for accuracy relying on a set of unlabelled real wor...
Context: Deep Neural Networks (DNN) have shown great promise in various domains, for example to supp...
In this study, an enhanced correlation-test-based validation procedure is developed to check the qua...
This is the first version of the codes for our outcoming paper: Correlations Between Deep Neural Net...
DNN testing is one of the most effective methods to guarantee the quality of DNN. In DNN testing, ma...
Generating test cases and further evaluating their "quality" are two critical topics in the area of ...
Correlation of the QTc model and the Deep Neural Network (Deep Convolutional Network).</p
Deep neural networks (DNNs) have a wide range of applications, and software employing them must be t...
This paper summarizes eight design requirements for DNN testing criteria, taking into account distri...
Deep neural networks (DNNs) have a wide range of applications, and software employing them must be t...
Corresponding code to the paper "Is Neuron Coverage a Meaningful Measure for Testing Deep Neural Net...
Concolic testing combines program execution and symbolic analysis to explore the execution paths of ...
A) Spearman’s correlation of all DNN RDMs at a given layer of the encoder with other DNN RDMs comput...
This is a graphical representation of a standard feedforward DNN architecture. The DNN is fed with a...
Despite the large number of sophisticated deep neural network (DNN) verification algorithms, DNN ver...
Deep Neural Networks (DNN) are typically tested for accuracy relying on a set of unlabelled real wor...
Context: Deep Neural Networks (DNN) have shown great promise in various domains, for example to supp...
In this study, an enhanced correlation-test-based validation procedure is developed to check the qua...
This is the first version of the codes for our outcoming paper: Correlations Between Deep Neural Net...
DNN testing is one of the most effective methods to guarantee the quality of DNN. In DNN testing, ma...
Generating test cases and further evaluating their "quality" are two critical topics in the area of ...
Correlation of the QTc model and the Deep Neural Network (Deep Convolutional Network).</p
Deep neural networks (DNNs) have a wide range of applications, and software employing them must be t...
This paper summarizes eight design requirements for DNN testing criteria, taking into account distri...
Deep neural networks (DNNs) have a wide range of applications, and software employing them must be t...
Corresponding code to the paper "Is Neuron Coverage a Meaningful Measure for Testing Deep Neural Net...
Concolic testing combines program execution and symbolic analysis to explore the execution paths of ...
A) Spearman’s correlation of all DNN RDMs at a given layer of the encoder with other DNN RDMs comput...
This is a graphical representation of a standard feedforward DNN architecture. The DNN is fed with a...
Despite the large number of sophisticated deep neural network (DNN) verification algorithms, DNN ver...
Deep Neural Networks (DNN) are typically tested for accuracy relying on a set of unlabelled real wor...
Context: Deep Neural Networks (DNN) have shown great promise in various domains, for example to supp...
In this study, an enhanced correlation-test-based validation procedure is developed to check the qua...
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