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Qianmu Xiao and Liang Zhao
Acquiring relevant, high-quality, and heterogeneous medical images is essential in various types of automated analysis, used for a variety of downstream data augmentation tasks. However, a large number of real image samples are expensive to obtain, espec...
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Yu Cao, Kan Ni, Xiongwen Jiang, Taiga Kuroiwa, Haohao Zhang, Takahiro Kawaguchi, Seiji Hashimoto and Wei Jiang
The potential of autonomous driving technology to revolutionize the transportation industry has attracted significant attention. Path following, a fundamental task in autonomous driving, involves accurately and safely guiding a vehicle along a specified ...
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Xiaohan Xu, Xudong Huang, Dianfang Bi and Ming Zhou
Aerodynamic compressor designs require considerable prior knowledge and a deep understanding of complex flow fields. With the development of computer science, artificial intelligence (AI) has been widely applied to compressors design. Among the various A...
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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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Xiaoping Zhang, Yuanpeng Zheng, Li Wang, Arsen Abdulali and Fumiya Iida
Multi-agent collaborative target search is one of the main challenges in the multi-agent field, and deep reinforcement learning (DRL) is a good way to learn such a task. However, DRL always faces the problem of sparse reward, which to some extent reduces...
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