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Duo Sun, Lei Zhang, Kai Jin, Jiasheng Ling and Xiaoyuan Zheng
Aiming at the imbalance of industrial control system data and the poor detection effect of industrial control intrusion detection systems on network attack traffic problems, we propose an ETM-TBD model based on hybrid machine learning and neural network ...
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Ruikui Ma, Qiuqian Wang, Xiangxi Bu and Xuebin Chen
With the development of the Internet of Things, a huge number of devices are connected to the network, network traffic is exhibiting massive and low latency characteristics. At the same time, it is becoming cheaper and cheaper to launch DDoS attacks, and...
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Linkai Peng, Yingming Gao, Rian Bao, Ya Li and Jinsong Zhang
As an indispensable module of computer-aided pronunciation training (CAPT) systems, mispronunciation detection and diagnosis (MDD) techniques have attracted a lot of attention from academia and industry over the past decade. To train robust MDD models, t...
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Imran, Megat Farez Azril Zuhairi, Syed Mubashir Ali, Zeeshan Shahid, Muhammad Mansoor Alam and Mazliham Mohd Su?ud
Anomaly detection (AD) has captured a significant amount of focus from the research field in recent years, with the rise of the Internet of Things (IoT) application. Anomalies, often known as outliers, are defined as the discovery of anomalous occurrence...
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Yi-Quan Li, Hao-Sen Chang and Daw-Tung Lin
In the field of computer vision, large-scale image classification tasks are both important and highly challenging. With the ongoing advances in deep learning and optical character recognition (OCR) technologies, neural networks designed to perform large-...
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