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检索条件"机构=The Henan Key Laboratory of Brain Science and Brain Computer Interface Technology"
920 条 记 录,以下是641-650 订阅
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Is Dataset Quality Still a Concern in Diagnosis Using Large Foundation Model?
arXiv
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arXiv 2024年
作者: Lin, Ziqin Li, Heng Li, Zinan Fu, Huazhu Liu, Jiang Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Institute of High Performance Computing Agency for Science Technology and Research Singapore Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Southern University of Science and Technology Shenzhen China
Recent advancements in pre-trained large foundation models (LFM) have yielded significant breakthroughs across various domains, including natural language processing and computer vision. These models have been particu... 详细信息
来源: 评论
Multi-Objective Archiving
arXiv
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arXiv 2023年
作者: Li, Miqing López-Ibáñez, Manuel Yao, Xin The School of Computer Science University of Birmingham United Kingdom Alliance Manchester Business School University of Manchester United Kingdom The Research Institute of Trustworthy Autonomous Systems Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China
Most multi-objective optimisation algorithms maintain an archive explicitly or implicitly during their search. Such an archive can be solely used to store high-quality solutions presented to the decision maker, but in... 详细信息
来源: 评论
Examination of the Multimodal Nature of Multi-Objective Neural Architecture Search
Examination of the Multimodal Nature of Multi-Objective Neur...
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IEEE Symposium Series on Computational Intelligence (SSCI)
作者: Cheng Gong Yang Nan Lie Meng Pang Hisao Ishibuchi Qingfu Zhang Department of Computer Science and Engineering Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Southern University of Science and Technology Shenzhen China Department of Computer Science City University of Hong Kong Kowloon Tong Hong Kong The City University of Hong Kong Shenzhen Research Institute Shenzhen China
Remarkable successes in deep learning have spurred significant growth in the field of neural architecture search (NAS), which is rapidly advancing as a promising technique for automating the design of network architec...
来源: 评论
Distortion-adaptive salient object detection in 360◦ omnidirectional images
arXiv
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arXiv 2019年
作者: Li, Jia Su, Jinming Xia, Changqun Tian, Yonghong State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China Beijing Adavanced Innovation Center for Big Data and Brain Computing Beihang University China National Engineering Laboratory for Video Technology School of Electronics Engineering and Computer Science Peking University Beijing China Peng Cheng Laboratory Shenzhen518000 China
Image-based salient object detection (SOD) has been extensively explored in the past decades. However, SOD on 360◦ omnidirectional images is less studied owing to the lack of datasets with pixel-level annotations. Tow... 详细信息
来源: 评论
Precise nanomedicine for intelligent therapy of cancer
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science China Chemistry 2018年 第12期61卷 1503-1552页
作者: Huabing Chen Zhanjun Gu Hongwei An Chunying Chen Jie Chen Ran Cui Siqin Chen Weihai Chen Xuesi Chen Xiaoyuan Chen Zhuo Chen Baoquan Ding Qian Dong Qin Fan Ting Fu Dayong Hou Qiao Jiang Hengte Ke Xiqun Jiang Gang Liu Suping Li Tianyu Li Zhuang Liu Guangjun Nie Muhammad Ovais Daiwen Pang Nasha Qiu Youqing Shen Huayu Tian Chao Wang Hao Wang Ziqi Wang Huaping Xu Jiang-Fei Xu Xiangliang Yang Shuang Zhu Xianchuang Zheng Xianzheng Zhang Yanbing Zhao Weihong Tan Xi Zhang Yuliang Zhao State Key Laboratoiy of Radiation Medicine and Protection Jiangsu Key Laboratoiy of Neuropsychiatric Diseases College of Pharmaceutical Sciences Soochow University Suzhou 215123 China Key Laboratoiy of Biomedical Polymers of Ministry of Education Department of Chemistiy Wuhan University Wuhan 430072 China Laboratoiy of Molecular Imaging and Nanomedicine National Institute of Biomedical Imaging and Bioengineering National Institutes of Health Bethesda MD 20892 USA Molecular Science and Biomedicine Laboratoiy State Key Laboratory of Chemo/Bio-Sensing and Chemometrics College of Chemistiy and Chemical Engineering Aptamer Engineering Center of Hunan Province Hunan University Changsha 410082 China Jiangsu Key Laboratoiy for Carbon-Based Functional Materials & Devices Institute of Functional Nano & Soft Materials Soochow University Suzhou 215123 China Department of Polymer Science and Engineering College cf Chemistry and Chemical Engineering Nanjing University Nanjing 210093 China State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics & Center for Molecular Imaging and Translational Medicine School of Public Health Xiamen University Xiamen 361102 China Department of Chemistiy Tsinghua University Beijing 100084 China National Engineering Research Center for Nanomedicine College of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074 China Department of Chemistiy and Department of Physiology and Functional Genomics Center for Research at Bio/nano Interface Health Cancer Center UF Genetics Institute and McKnight Brain Institute University of Florida Gainesville FL 32611-7200 USA institute of High Energy Physics Chinese Academy of Sciences Beijing 100049 China CAS Key Laboratoiy for Biomedical Effects of Nanomaterials and Nanosafety CAS Center for Excellence in Nanoscience National Center for Nanoscience and Technology of China Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China Key Labo
Precise nanomedicine has been extensively explored for efficient cancer imaging and targeted cancer therapy, as evidenced by a few breakthroughs in their preclinical and clinical explorations. Here, we demonstrate the... 详细信息
来源: 评论
Keiki: Towards realistic danmaku generation via sequential GANs
arXiv
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arXiv 2021年
作者: Wang, Ziqi Liu, Jialin Yannakakis, Georgios N. Research Institute of Trustworthy Autonomous System Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Institute of Digital Games University of Malta Msida2080 Malta
Search-based procedural content generation methods have recently been introduced for the autonomous creation of bullet hell games. Search-based methods, however, can hardly model patterns of danmakus—the bullet hell ... 详细信息
来源: 评论
Emergence and reconfiguration of modular structure for synaptic neural networks during continual familiarity detection
arXiv
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arXiv 2023年
作者: Gu, Shi Mattar, Marcelo G. Tang, Huajin Pan, Gang School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China Shenzhen China Psychology Department New York University United States College of Computer Science and Technology Zhejiang University Hangzhou China State Key Laboratory of Brain Machine Intelligence Zhejiang University Hangzhou China
While advances in artificial intelligence and neuroscience have enabled the emergence of neural networks capable of learning a wide variety of tasks, our understanding of the temporal dynamics of these networks remain... 详细信息
来源: 评论
Personalized Sleep Staging Leveraging Source-free Unsupervised Domain Adaptation
arXiv
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arXiv 2024年
作者: Zhou, Yangxuan Zhao, Sha Wang, Jiquan Jiang, Haiteng Li, Shijian Luo, Benyan Li, Tao Pan, Gang State Key Laboratory of Brain-machine Intelligence Zhejiang University Hangzhou China College of Computer Science and Technology Zhejiang University Hangzhou China Department of Neurobiology Affiliated Mental Health Center Hangzhou Seventh People’s Hospital Zhejiang University School of Medicine Hangzhou China MOE Frontier Science Center for Brain Science and Brain-machine Integration Zhejiang University Hangzhou China The First Affiliated Hospital College of Medicine Zhejiang University Hangzhou China
Sleep staging is important for monitoring sleep quality and diagnosing sleep-related disorders. Recently, numerous deep learning-based models have been proposed for automatic sleep staging using polysomnography record... 详细信息
来源: 评论
Initial Populations with a Few Heuristic Solutions Significantly Improve Evolutionary Multi-Objective Combinatorial Optimization
Initial Populations with a Few Heuristic Solutions Significa...
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IEEE Symposium Series on Computational Intelligence (SSCI)
作者: Cheng Gong Yang Nan Lie Meng Pang Hisao Ishibuchi Qingfu Zhang Department of Computer Science and Engineering Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Southern University of Science and Technology Shenzhen China Department of Computer Science City University of Hong Kong Kowloon Tong Hong Kong The City University of Hong Kong Shenzhen Research Institute Shenzhen China
Population initialization is a crucial and essential step in evolutionary multi-objective optimization (EMO) algorithms. The quality of the generated initial population can significantly affect the performance of an E...
来源: 评论
Evolutionary Reinforcement Learning via Cooperative Coevolution
arXiv
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arXiv 2024年
作者: Hu, Chengpeng Liu, Jialin Yao, Xin Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Research Institute of Trustworthy Autonomous System Southern University of Science and Technology Shenzhen China Department of Computing and Decision Sciences Lingnan University Hong Kong
Recently, evolutionary reinforcement learning has obtained much attention in various domains. Maintaining a population of actors, evolutionary reinforcement learning utilises the collected experiences to improve the b...
来源: 评论