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Octavio Delgadillo, Bernhard Blieninger, Juri Kuhn and Uwe Baumgarten
Consolidating tasks to a smaller number of electronic control units (ECUs) is an important strategy for optimizing costs and resources in the automotive industry. In our research, we aim to enable ECU consolidation by migrating tasks at runtime between d...
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Tianyu Yang, Xin Wang and Zhengjiang Liu
With the aim to solve the problem of missing or tampering of ship type information in AIS information, in this paper, a novel ship type recognition scheme based on ship navigating trajectory and convolutional neural network (CNN) is proposed. Firstly, ac...
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Yufeng Huang, Jun Tao, Gang Sun, Hao Zhang and Yan Hu
In this study, a prognostics and health management (PHM) framework is proposed for aero-engines, which combines a dynamic probability (DP) model and a long short-term memory neural network (LSTM). A DP model based on Gaussian mixture model-adaptive densi...
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Daniel Turner, Pedro J. S. Cardoso and João M. F. Rodrigues
Learning to recognize a new object after having learned to recognize other objects may be a simple task for a human, but not for machines. The present go-to approaches for teaching a machine to recognize a set of objects are based on the use of deep neur...
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Yangmin Li, Yugang Liu, and Xiaoping Liu
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