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Res-EMSA: Adaptive Adjustment of Innovation Based on Efficient Multihead Self-Attention in GNSS/INS Tightly Integrated Navigation System 期刊论文
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2024, 卷号: 21, 页码: 5
作者:  Xu, Hongfu;  Luo, Haiyong;  Wu, Zijian;  Zhao, Fang
收藏  |  浏览/下载：0/0  |  提交时间：2024/05/20
Technological innovation  Global navigation satellite system  Navigation  Feature extraction  Adaptation models  Measurement uncertainty  Kalman filters  Deep learning  extended Kalman filter (EKF)  innovation matrix  integrated navigation  
Lightweight Multiattention Recursive Residual CNN-Based In-Loop Filter Driven by Neuron Diversity 期刊论文
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2023, 卷号: 33, 期号: 11, 页码: 6996-7008
作者:  Li, Mingxuan;  Ji, Wen
收藏  |  浏览/下载：0/0  |  提交时间：2024/05/20
Video coding  in-loop filtering  convolutional neural network  deep learning  high-efficiency video coding (HEVC)  
Mining collaborative spatio-temporal clues for face forgery detection 期刊论文
MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 页码: 20
作者:  Ding, Bo;  Fan, Zhenfeng;  Zhao, Zejun;  Xia, Shihong
收藏  |  浏览/下载：6/0  |  提交时间：2023/12/04
Face forgery detection  Spatial-temporal clue  Low-level feature  Collaborative learning  Multimodel attention  
Towards Predicting the Measurement Noise Covariance with a Transformer and Residual Denoising Autoencoder for GNSS/INS Tightly-Coupled Integrated Navigation 期刊论文
REMOTE SENSING, 2022, 卷号: 14, 期号: 7, 页码: 22
作者:  Xu, Hongfu;  Luo, Haiyong;  Wu, Zijian;  Wu, Fan;  Bao, Linfeng;  Zhao, Fang
收藏  |  浏览/下载：17/0  |  提交时间：2022/12/07
tightly coupled integrated navigation  measurement noise estimation  transformer  adaptive Kalman filtering  
Limited View Tomographic Reconstruction Using a Cascaded Residual Dense Spatial-Channel Attention Network With Projection Data Fidelity Layer 期刊论文
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2021, 卷号: 40, 期号: 7, 页码: 1792-1804
作者:  Zhou, Bo;  Zhou, S. Kevin;  Duncan, James S.;  Liu, Chi
收藏  |  浏览/下载：29/0  |  提交时间：2021/12/01
Tomographic reconstruction  cascaded network  projection data fidelity layer  RedSCAN  limited angle  sparse view  
Two-stream deep sparse network for accurate and efficient image restoration 期刊论文
COMPUTER VISION AND IMAGE UNDERSTANDING, 2020, 卷号: 200, 页码: 11
作者:  Wang, Shuhui;  Hu, Ling;  Li, Liang;  Zhang, Weigang;  Huang, Qingming
收藏  |  浏览/下载：291/0  |  提交时间：2020/12/10
Two-stream sparse network  Image restoration  Image super-resolution  Image denoising  
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  
A deep attention-based ensemble network for real-time face hallucination 期刊论文
JOURNAL OF REAL-TIME IMAGE PROCESSING, 2020, 页码: 11
作者:  Liu, Dongdong;  Chen, Jincai;  Huang, Zhenxing;  Zeng, Ni;  Lu, Ping;  Yang, Lin;  Wang, Haofeng;  Kou, Jinqiao;  Wu, Min
收藏  |  浏览/下载：58/0  |  提交时间：2020/12/10
Face hallucination  Attention mechanism  Residual learning  Ensemble model  
ADST: Forecasting Metro Flow Using Attention-Based Deep Spatial-Temporal Networks with Multi-Task Learning 期刊论文
SENSORS, 2020, 卷号: 20, 期号: 16, 页码: 23
作者:  Jia, Hongwei;  Luo, Haiyong;  Wang, Hao;  Zhao, Fang;  Ke, Qixue;  Wu, Mingyao;  Zhao, Yunyun
收藏  |  浏览/下载：48/0  |  提交时间：2020/12/10
forecasting passenger flow  spatiotemporal networks  multi-task learning  attention mechanism  spatiotemporal dependency  
Saliency Prediction Network for 360 degrees Videos 期刊论文
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2020, 卷号: 14, 期号: 1, 页码: 27-37
作者:  Zhang, Youqiang;  Dai, Feng;  Ma, Yike;  Li, Hongliang;  Zhao, Qiang;  Zhang, Yongdong
收藏  |  浏览/下载：39/0  |  提交时间：2020/12/10
Saliency prediction  360 degrees videos  cube map  optical flow  global feature  Gaussian priors  residual attention