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兰州理工大学 [32]

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	A remaining useful life prediction method based on time–frequency images of the mechanical vibration signals 期刊论文 Measurement: Journal of the International Measurement Confederation, 2022, 卷号: 202 作者: Du, Xianjun; Jia, Wenchao; Yu, Ping; Shi, Yaoke; Cheng, Shengyi 收藏 \| 浏览/下载：32/0 \| 提交时间：2022/09/22 Convolution Forecasting Preventive maintenance Rotating machinery Vibrations (mechanical) Wavelet transforms Attention mechanisms Continuous Wavelet Transform Convolutional neural network Degradation trend Feature map Remaining useful life predictions Rolling bearings Spectral feature Time frequency Time–frequency spectral feature map
	Membrane fouling diagnosis of membrane components based on multi-feature information fusion 期刊论文 JOURNAL OF MEMBRANE SCIENCE, 2022, 卷号: 657 作者: Shi, Yaoke; Wang, Zhiwen; Du, Xianjun; Gong, Bin; Lu, Yanrong 收藏 \| 浏览/下载：22/0 \| 提交时间：2022/07/19 MBR CBAM-MUL-CNN Feature fusion Attention mechanism Membrane fouling diagnosis
	Research on Video Captioning Based on Multifeature Fusion 期刊论文 Computational Intelligence and Neuroscience, 2022, 卷号: 2022 作者: Zhao, Hong; Guo, Lan; Chen, ZhiWen; Zheng, HouZe 收藏 \| 浏览/下载：24/0 \| 提交时间：2022/06/20 Embedded layers Frame features Incomplete information Large-scale datasets Mode features Multi-feature fusion Performance Pre-training Single mode Video frame
	Mechanical Fault Diagnosis Method Based on Multi-sensor Signal Feature Fusion Using Deep Convolutional Neural Network 期刊论文 Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2021, 卷号: 41, 期号: 2, 页码: 362-369 and 416 作者: Wu, Yaochun; Zhao, Rongzhen; Jin, Wuyin; He, Tianjing; Wu, Jie 收藏 \| 浏览/下载：16/0 \| 提交时间：2022/02/17 Complex networks Convolution Convolutional neural networks Deep neural networks Failure analysis Fault detection Fault classification Feature representation Hierarchical fusions Mechanical fault diagnosis Multi-sensor information fusion Multisensor data fusion One-dimensional features Softmax regressions
	Multi-format speech BioHashing based on energy to zero ratio and improved LP-MMSE parameter fusion 期刊论文 Multimedia Tools and Applications, 2021, 卷号: 80, 期号: 7, 页码: 10013-10036 作者: Wang, Yong; Huang, Yi-bo; Zhang, Ran; Zhang, Qiu-yu 收藏 \| 浏览/下载：12/0 \| 提交时间：2021/06/03 Authentication Chaotic systems Mean square error Application range Covariance method Detection and localization Linear prediction Minimum mean square errors Real time performance Time-frequency parameter Zero crossing rate
	Method of fault identification based on fusion of CEEMD_MPE and GK fuzzy clustering 期刊论文 Zhendong Gongcheng Xuebao/Journal of Vibration Engineering, 2020, 卷号: 33, 期号: 3, 页码: 629-635 作者: Zhao, Rong-Zhen; Sun, Ze-Jin 收藏 \| 浏览/下载：3/0 \| 提交时间：2020/11/14 Entropy Fuzzy clustering Signal processing Correlation coefficient Dimension reduction Empirical Mode Decomposition Ensemble empirical mode decomposition Fault feature extractions Fault identifications Mode combination method Non stationary characteristics
	A spatial moving target recognition algorithm based on full information vector 会议论文作者: Du, Yun; Wen, Desheng; Liu, Guizhong; Yi, Hongwei; Liu, Meiying 收藏 \| 浏览/下载：23/0 \| 提交时间：2019/11/15 moving target full information vector recognition Gauss distribution
	Combine edge feature based on luminance component and texture feature for image quality evaluation 期刊论文 Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), 2019, 卷号: 49, 期号: 1, 页码: 283-289 作者: Hu, Wen-Jin; Cao, Xin; Ye, Yu-Qi 收藏 \| 浏览/下载：17/0 \| 提交时间：2020/11/14 Computer applications Image fusion Image texture Luminance Quality control Textures Edge features Image quality evaluation Luminance component Multi-feature fusion Texture features
	Convolutional Residual Learning with Sparse Robust Samples and Multi-feature Fusion for Object Tracking 会议论文作者: Gao, Huiling; Liu, Jie 收藏 \| 浏览/下载：1/0 \| 提交时间：2019/11/15 Sparse representation deep learning joint detection multiple feature fusion object tracking
	Convolutional residual learning with sparse robust samples and multi-feature fusion for object tracking 会议论文 Chengdu, China, December 12, 2018 - December 14, 2018 作者: Gao, Huiling; Liu, Jie; Liu, Chaorong; Li, Binshan; Zhao, Zhengtian 收藏 \| 浏览/下载：16/0 \| 提交时间：2020/11/15 Convolution Deep learning Interactive computer systems Tracking (position) Contamination degree Joint detection Multi-feature fusion Multiple feature fusion Object Tracking Occlusion detection Positioning accuracy Sparse representation

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