Search Results

In recent years, Deep Learning (DL) applications in JavaScript environment have become increasingly popular. As the infrastructure for DL applications, JavaScript DL frameworks play a crucial role in the development and deployment. It is essential to ...

Machine translation systems have been widely adopted in our daily life, making life easier and more convenient. Unfortunately, erroneous translations may result in severe consequences, such as financial losses. This requires to improve the accuracy and ...

Deep learning (DL) libraries have become the key component in developing and deploying DL-based software nowadays. With the growing popularity of applying DL models in both academia and industry across various domains, any bugs inherent in the DL ...

Deep learning frameworks are the foundation of deep learning model construction and inference. Many testing methods using deep learning models as test inputs are proposed to ensure the quality of deep learning frameworks. However, there are still ...

• We propose Ramos, a hierarchical heuristic DL framework testing method.
• Ramos detects 15 crashes and 154 precision bugs under three widely-used frameworks, and 14 of these crashes are confirmed.
• We design a hierarchical structure ...

With the application of deep learning (DL) in signal detection, improving the robustness of classification models has received much attention, especially in automatic modulation classification (AMC) of electromagnetic signals. A large amount of ...

Point clouds have been widely used in a large number of application scenarios to handle with various deep learning (DL) tasks. Testing is an essential means to guarantee the robustness of DL models, which places high demands on test data. Therefore, it ...

With the rapid development of object detection in deep learning (DL), applications on LiDAR point clouds have received much attention, such as autonomous driving. To verify the robustness of object detection models by testing, large amounts of ...

Deep learning has made great progress in medical diagnosis. However, due to data standardization and privacy restriction, the acquisition and sharing of medical image data have been hindered, leading to the unacceptable accuracy of some intelligent ...

Deep learning(DL) techniques attract people from various fields with superior performance in making progressive breakthroughs. To ensure the quality of DL techniques, researchers have been working on testing and verification approaches. Some recent ...