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Chinyang Henry Tseng, Woei-Jiunn Tsaur and Yueh-Mao Shen
In detecting large-scale attacks, deep neural networks (DNNs) are an effective approach based on high-quality training data samples. Feature selection and feature extraction are the primary approaches for data quality enhancement for high-accuracy intrus...
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Mohammed Saïd Kasttet, Abdelouahid Lyhyaoui, Douae Zbakh, Adil Aramja and Abderazzek Kachkari
Recently, artificial intelligence and data science have witnessed dramatic progress and rapid growth, especially Automatic Speech Recognition (ASR) technology based on Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs). Consequently, new end-to-...
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Linfei Hou, Honglin Liu, Ting Yang, Shuaibin An and Rui Wang
In addressing the morphing problem in vehicle flight, some scholars have primarily employed reinforcement learning methods to make morphing decisions based on task. However, they have not considered the constraints associated with the task process. The i...
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Tao Jin, Wen Zhang, Chunlai Chen, Bin Chen, Yizhou Zhuang and He Zhang
Deep-learning- and unmanned aerial vehicle (UAV)-based methods facilitate structural crack detection for tall structures. However, contemporary datasets are generally established using images taken with handheld or vehicle-mounted cameras. Thus, these im...
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Xuan Di, Rongye Shi, Zhaobin Mo and Yongjie Fu
For its robust predictive power (compared to pure physics-based models) and sample-efficient training (compared to pure deep learning models), physics-informed deep learning (PIDL), a paradigm hybridizing physics-based models and deep neural networks (DN...
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Mahmoud Elmezain, Majed M. Alwateer, Rasha El-Agamy, Elsayed Atlam and Hani M. Ibrahim
Automatic key gesture detection and recognition are difficult tasks in Human?Computer Interaction due to the need to spot the start and the end points of the gesture of interest. By integrating Hidden Markov Models (HMMs) and Deep Neural Networks (DNNs),...
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Abubakar Ahmad Musa, Adamu Hussaini, Weixian Liao, Fan Liang and Wei Yu
Cyber-physical systems (CPS) refer to systems that integrate communication, control, and computational elements into physical processes to facilitate the control of physical systems and effective monitoring. The systems are designed to interact with the ...
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Haochen Li, Haibing Chen, Chengpeng Tan, Zaiming Jiang and Xinyi Xu
Optimal entry flight of hypersonic vehicles requires achieving specific mission objectives under complex nonlinear flight dynamics constraints. The challenge lies in rapid generation of optimal or near-optimal flight trajectories with significant changes...
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Zhe Liu, Jie Yan, Bangcheng Ai, Yonghua Fan, Kai Luo, Guodong Cai and Jiankai Qin
This paper presents a deep neural network-based online trajectory generation method for the aerodynamic characteristic description and terminal-area energy management of wave-rider aircrafts. First, the flight dynamics equations in the energy domain are ...
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Zhuo Li, Hengyi Li and Lin Meng
Currently, with the rapid development of deep learning, deep neural networks (DNNs) have been widely applied in various computer vision tasks. However, in the pursuit of performance, advanced DNN models have become more complex, which has led to a large ...
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