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Wen-Chang Cheng, Hung-Chou Hsiao, Yung-Fa Huang and Li-Hua Li
This research proposes a single network model architecture for mask face recognition using the FaceNet training method. Three pre-trained convolutional neural networks of different sizes are combined, namely InceptionResNetV2, InceptionV3, and MobileNetV...
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Qingqing Hong, Xinyi Zhong, Weitong Chen, Zhenghua Zhang and Bin Li
Hyperspectral images (HSIs) are pivotal in various fields due to their rich spectral?spatial information. While convolutional neural networks (CNNs) have notably enhanced HSI classification, they often generate redundant spatial features. To address this...
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Ru Ye, Hongyan Xing and Xing Zhou
Addressing the limitations of manually extracting features from small maritime target signals, this paper explores Markov transition fields and convolutional neural networks, proposing a detection method for small targets based on an improved Markov tran...
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Xin Tong, Bo Jin, Jingya Wang, Ying Yang, Qiwei Suo and Yong Wu
In recent years, the number of malicious web pages has increased dramatically, posing a great challenge to network security. While current machine learning-based detection methods have emerged as a promising alternative to traditional detection technique...
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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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Arfan Haider Wahla, Lan Chen, Yali Wang and Rong Chen
Automatic Classification of Wireless Signals (ACWS), which is an intermediate step between signal detection and demodulation, is investigated in this paper. ACWS plays a crucial role in several military and non-military applications, by identifying inter...
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