CSpace

浏览/检索结果: 共9条,第1-9条 帮助

已选(0)清除 条数/页:   排序方式:
Tactile-Based Fabric Defect Detection Using Convolutional Neural Network With Attention Mechanism 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022, 卷号: 71, 页码: 9
作者:  Bin Fang;  Long, Xingming;  Sun, Fuchun;  Liu, Huaping;  Zhang, Shixin;  Fang, Cheng
收藏  |  浏览/下载:20/0  |  提交时间:2022/12/07
Fabrics  Feature extraction  Frequency-domain analysis  Tactile sensors  Cameras  Visualization  Sensors  Attention mechanism  defect detection  vision-based tactile sensor  
Predicting the Noise Covariance With a Multitask Learning Model for Kalman Filter-Based GNSS/INS Integrated Navigation 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2021, 卷号: 70, 页码: 13
作者:  Wu, Fan;  Luo, Haiyong;  Jia, Hongwei;  Zhao, Fang;  Xiao, Yimin;  Gao, Xile
收藏  |  浏览/下载:34/0  |  提交时间:2021/12/01
Adaptive integrated navigation  deep learning  denoising autoencoder (DAE)  Kalman filter (KF)  measurement noise  process noise  
Heterogeneous Multi-Task Learning for Multiple Pseudo-Measurement Estimation to Bridge GPS Outages 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2021, 卷号: 70, 页码: 16
作者:  Lu, Shuangqiu;  Gong, Yilin;  Luo, Haiyong;  Zhao, Fang;  Li, Zhaohui;  Jiang, Jinguang
收藏  |  浏览/下载:27/0  |  提交时间:2021/12/01
Artificial intelligence (AI) and neural networks (NNs)  global position system (GPS) outages  inertial navigation system (INS)/GPS integrated navigation  multi-task learning (MTL)  multiple pseudo-measurement estimation  
A Spatial-Temporal Positioning Algorithm Using Residual Network and LSTM 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2020, 卷号: 69, 期号: 11, 页码: 9251-9261
作者:  Wang, Rongrong;  Luo, Haiyong;  Wang, Qu;  Li, Zhaohui;  Zhao, Fang;  Huang, Jingyu
收藏  |  浏览/下载:139/0  |  提交时间:2020/12/10
Wireless fidelity  Feature extraction  Fingerprint recognition  Residual neural networks  Deep learning  Robustness  Degradation  Convolutional neural network (CNN)  indoor positioning  long short-term memory (LSTM)  residual network  spatial-temporal  
Binary Volumetric Convolutional Neural Networks for 3-D Object Recognition 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2019, 卷号: 68, 期号: 1, 页码: 38-48
作者:  Ma, Chao;  Guo, Yulan;  Lei, Yinjie;  An, Wei
收藏  |  浏览/下载:269/0  |  提交时间:2019/04/03
3-D object recognition  convolutional neural network (CNN)  deep learning (DL)  network binarization  volumetric representation  
Object Tracking Using Multiple Features and Adaptive Model Updating 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2017, 卷号: 66, 期号: 11, 页码: 2882-2897
作者:  Hu, Qingyong;  Guo, Yulan;  Lin, Zaiping;  An, Wei;  Cheng, Hongwei
收藏  |  浏览/下载:56/0  |  提交时间:2019/12/12
Adaptive model updating  correlation filters  multiple feature integration  object tracking  
Measurement of Duration, Energy of Instantaneous Frequencies, and Splits of Subcomponents of the Second Heart Sound 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2015, 卷号: 64, 期号: 7, 页码: 1958-1967
作者:  Barma, Shovan;  Chen, Bo-Wei;  Ji, Wen;  Jiang, Feng;  Wang, Jhing-Fa
收藏  |  浏览/下载:37/0  |  提交时间:2019/12/13
Duration estimation of second heart sound (S2)  identification of abnormal splits of S2  S2  signal-change point detection  split measurement of S2  
Dynamic compensation of Nonlinear sensors by a learning-from-examples approach 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2008, 卷号: 57, 期号: 8, 页码: 1689-1694
作者:  Marconato, Anna;  Hu, Mingqing;  Boni, Andrea;  Petri, Dario
收藏  |  浏览/下载:34/0  |  提交时间:2019/12/16
dynamic compensation  low power  microcontroller implementation  reduced-set methods  support vector machines for regression (SVRs)  wireless sensor networks (WSNs)  
Embedded test resource for SoC to reduce required tester channels based on advanced convolutional codes 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2006, 卷号: 55, 期号: 2, 页码: 389-399
作者:  Han, YH;  Li, XW;  Li, HW;  Chandra, A
收藏  |  浏览/下载:37/0  |  提交时间:2019/12/16
automatic test equipment  convolutional code  diagnosis  error cancellation  masking  unknown bits (X-bits)