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基于主方向傅里叶变换的2D 3D脊柱图像分级配准方法研究 学位论文
硕士, 沈阳: 中国科学院沈阳自动化研究所, 2021
Authors:  杨克克
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2D/3D配准  傅里叶变换  分级配准框架  图像分割  
面向无人艇的障碍物与船只目标检测方法研究 学位论文
硕士, 沈阳: 中国科学院沈阳自动化研究所, 2021
Authors:  马莹
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障碍物检测  船只目标检测  概率图模型  视觉显著性  YOLO  
Tracking-by-Counting: Using Network Flows on Crowd Density Maps for Tracking Multiple Targets 期刊论文
IEEE Transactions on Image Processing, 2021, 卷号: 30, 页码: 1439-1452
Authors:  Ren WH(任卫红);  Wang, Xinchao;  Tian JD(田建东);  Tang YD(唐延东);  Chan, Antoni B.
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People tracking  crowd density map  multiple people tracking  flow tracking  
Semantic mapping for mobile robots in indoor scenes: A survey 期刊论文
Information (Switzerland), 2021, 卷号: 12, 期号: 2, 页码: 1-14
Authors:  Han XN(韩小宁);  Li SL(李帅龙);  Wang XH(王晓辉)
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Acquisition of semantic information  Indoor scenes  Map representation  Mobile robots  Semantic mapping  
Deep Learning for EMG-based Human-Machine Interaction: A Review 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2021, 卷号: 8, 期号: 3, 页码: 512-533
Authors:  Xiong DZ(熊德臻);  Zhang DH(张道辉);  Zhao XG(赵新刚);  Zhao YW(赵忆文)
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Accuracy  deep learning  electromyography (EMG)  human-machine interaction (HMI)  robustness  
Long-term correlations and multifractality of toll-free calls in China 期刊论文
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2021, 卷号: 567, 页码: 1-12
Authors:  Gui J(桂珺);  Zheng ZY(郑泽宇);  Fu DZ(付殿峥);  Fu Y(傅洋);  Liu Z(刘智)
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Calling activity  Long-term correlation  Multifractality  MFDFA  Scaling behavior  
A Comprehensive Review of Markov Random Field and Conditional Random Field Approaches in Pathology Image Analysis 期刊论文
Archives of Computational Methods in Engineering, 2021, 页码: 1-31
Authors:  Li, Yixin;  Li, Chen;  Li, Xiaoyan;  Wang K(王锴);  Rahaman, Md Mamunur;  Sun, Changhao;  Chen, Hao;  Wu, Xinran;  Zhang, Hong;  Wang, Qian
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基于卷积神经网络的跨镜多行人目标检测与跟踪方法研究 学位论文
博士, 沈阳: 中国科学院沈阳自动化研究所, 2020
Authors:  何淼
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行人检测  多目标跟踪  再识别  摄像机网络拓扑估计  跨镜多目标跟踪  
复杂交通环境下毫米波雷达多目标检测跟踪算法研究 学位论文
博士, 沈阳: 中国科学院沈阳自动化研究所, 2020
Authors:  高洁
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毫米波雷达  多目标检测  检测前跟踪  动态规划  运动模型  
Empirical Mode Decomposition and Temporal Convolutional Networks for Remaining Useful Life Estimation 期刊论文
INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING, 2020, 卷号: 48, 期号: 1, 页码: 61-79
Authors:  Yang, Wensi;  Yao QF(么庆丰);  Ye KJ(叶可江);  Xu CZ(须成忠)
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Convolutional neural networks  Empirical mode decomposition  Remaining useful life  Reliability