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Falah Amer Abdulazeez, Ismail Taha Ahmed and Baraa Tareq Hammad
A significant quantity of malware is created on purpose every day. Users of smartphones and computer networks now mostly worry about malware. These days, malware detection is a major concern in the cybersecurity area. Several factors can impact malware d...
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Pavlo Maruschak, Ihor Konovalenko, Yaroslav Osadtsa, Volodymyr Medvid, Oleksandr Shovkun, Denys Baran, Halyna Kozbur and Roman Mykhailyshyn
Modern neural networks have made great strides in recognising objects in images and are widely used in defect detection. However, the output of a neural network strongly depends on both the training dataset and the conditions under which the image was ac...
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Lei Yang, Mengxue Xu and Yunan He
Convolutional Neural Networks (CNNs) have become essential in deep learning applications, especially in computer vision, yet their complex internal mechanisms pose significant challenges to interpretability, crucial for ethical applications. Addressing t...
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Guoqing Dong, Weirong Li, Zhenzhen Dong, Cai Wang, Shihao Qian, Tianyang Zhang, Xueling Ma, Lu Zou, Keze Lin and Zhaoxia Liu
The developed prototype provides a more efficient and accurate solution for classifying dynagraph cards, meeting the requirements of oil field operations and enhancing economic benefits and work efficiency.
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JongBae Kim
This technology can prevent accidents involving large vehicles, such as trucks or buses, by selecting an optimal driving lane for safe autonomous driving. This paper proposes a method for detecting forward-driving vehicles within road images obtained fro...
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Jin-Woo Kong, Byoung-Doo Oh, Chulho Kim and Yu-Seop Kim
Intracerebral hemorrhage (ICH) is a severe cerebrovascular disorder that poses a life-threatening risk, necessitating swift diagnosis and treatment. While CT scans are the most effective diagnostic tool for detecting cerebral hemorrhage, their interpreta...
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Tatyana Aksenovich and Vasiliy Selivanov
During geomagnetic storms, which are a result of solar wind?s interaction with the Earth?s magnetosphere, geomagnetically induced currents (GICs) begin to flow in the long, high-voltage electrical networks on the Earth?s surface. It causes a number of ne...
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Shaoyan Zuo, Dazhi Wang, Xiao Wang, Liujia Suo, Shuaiwu Liu, Yongqing Zhao and Dewang Liu
In this study, a deep learning network for extracting spatial-temporal features is proposed to estimate significant wave height (????
H
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) and wave period (????
T
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) from X-band marine radar images. Since the shore-based radar image in this study is in...
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Diya Wang, Yonglin Zhang, Lixin Wu, Yupeng Tai, Haibin Wang, Jun Wang, Fabrice Meriaudeau and Fan Yang
In recent years, the study of deep learning techniques for underwater acoustic channel estimation has gained widespread attention. However, existing neural network channel estimation methods often overfit to training dataset noise levels, leading to dimi...
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Yong Liu, Xiaohui Yan, Wenying Du, Tianqi Zhang, Xiaopeng Bai and Ruichuan Nan
The current work proposes a novel super-resolution convolutional transposed network (SRCTN) deep learning architecture for downscaling daily climatic variables. The algorithm was established based on a super-resolution convolutional neural network with t...
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