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A Parallel Cerebrovascular Segmentation Algorithm Based on Focused Multi-Gaussians Model and Heterogeneous Markov Random Field
期刊论文
IEEE TRANSACTIONS ON NANOBIOSCIENCE, 2020, 卷号: 19, 期号: 3, 页码: 538-546
作者:
Lv, Zhilong
;
Mi, Fubo
;
Wu, Zhongke
;
Zhu, Yicheng
;
Liu, Xinyu
收藏
  |  
浏览/下载:24/0
  |  
提交时间:2020/12/10
Gaussian distribution
Image segmentation
Particle swarm optimization
Optimization
Histograms
Markov random fields
Robustness
Three-dimensional cerebrovascular segmentation
focused multi-Gaussians model
Chaotic oscillation particle swarm optimization
Markov random field
Color restoration of mural image based on double constrained convolutional neural network
期刊论文
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition), 2020, 卷号: 48, 期号: 6, 页码: 6-12
作者:
Xu, Zhigang
;
Yin, Wenyu
;
Zhu, Xufeng
收藏
  |  
浏览/下载:12/0
  |  
提交时间:2020/11/14
Color
Convolution
Convolutional neural networks
Discoloration
Markov processes
Multilayer neural networks
Restoration
Color features
Color restoration
Difference constraints
Global feature
Higher-order
Image-based
Local structure
Markov Random Fields
Predicting protein inter-residue contacts using composite likelihood maximization and deep learning
期刊论文
BMC BIOINFORMATICS, 2019, 卷号: 20, 期号: 1, 页码: 11
作者:
Zhang, Haicang
;
Zhang, Qi
;
Ju, Fusong
;
Zhu, Jianwei
;
Gao, Yujuan
收藏
  |  
浏览/下载:50/0
  |  
提交时间:2020/12/10
Residue-residue contacts prediction
Deep learning
Markov random fields
Composite likelihood maximization
A Markov Random Field and Adaptive Regularization Embedded Level Set Segmentation Model Solving by Graph Cuts.
期刊论文
Journal of Electrical & Computer Engineering, 2019, 页码: 1-13
作者:
Wang, Dengwei
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  |  
浏览/下载:5/0
  |  
提交时间:2019/12/17
MARKOV
random
fields
*IMAGE
segmentation
*REGULARIZATION
(Mathematics)
*MATHEMATICAL
optimization
*IMAGE
processing
Superpixel-based depth estimation for multiple view stereo
会议论文
2018 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2018, 2018-08-01
作者:
Yuan, D.
;
Liu, C.
;
Zhang, H.
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  |  
浏览/下载:14/0
  |  
提交时间:2019/12/30
Markov processes
Robotics
Stereo image processing
Superpixels
Textures
Boundary information
Depth Estimation
Depth information
Depth-map generation
Markov random fields models
Multiple views
Small region
Superpixel segmentations
Pixels
Continuous Probabilistic SLAM Solved via Iterated Conditional Modes
期刊论文
International Journal of Automation and Computing, 2019, 卷号: 16, 期号: 6, 页码: 838-850
作者:
J. Gimenez
;
A. Amicarelli
;
J. M. Toibero
;
F. di Sciascio
;
R. Carelli
收藏
  |  
浏览/下载:63/0
  |  
提交时间:2021/02/22
Probabilistic simultaneous localization and mapping (SLAM)
dynamic obstacles
Markov random fields (MRF)
iterated conditional modes (ICM)
kernel estimator.
Methods and datasets on semantic segmentation: A review
期刊论文
NEUROCOMPUTING, 2018, 卷号: 304, 页码: 82-103
作者:
Yu, Hongshan
;
Yang, Zhengeng
;
Tan, Lei
;
Wang, Yaonan
;
Sun, Wei
收藏
  |  
浏览/下载:13/0
  |  
提交时间:2021/02/02
Semantic segmentation
Convolutional neural network
Markov random fields
Weakly supervised method
3D point clouds labeling
Hyperspectral Image Classification With Markov Random Fields and a Convolutional Neural Network
期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 卷号: 27, 页码: 2354-2367
作者:
Cao, Xiangyong
;
Zhou, Feng
;
Xu, Lin
;
Meng, Deyu
;
Xu, Zongben
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2019/11/26
Hyperspectral image classification
Markov random fields
convolutional neural networks
Methods and datasets on semantic segmentation: A review
期刊论文
NEUROCOMPUTING, 2018, 卷号: 304, 页码: 82-103
作者:
Yu HS(余洪山)
;
Yang, Zhengeng
;
Tan, Lei
;
Wang YN(王耀南)
;
Sun, Wei
收藏
  |  
浏览/下载:61/0
  |  
提交时间:2018/06/17
Semantic segmentation
Convolutional neural network
Markov random fields
Weakly supervised method
3D point clouds labeling
An Approach to Locating Delayed Activities in Software Processes
期刊论文
International Journal of Automation and Computing, 2018, 卷号: 15, 期号: 1, 页码: 115-124
作者:
Yun-Zhi Jin
;
Hua Zhou
;
Hong-Ji Yang
;
Si-Jing Zhang
;
Ji-Dong Ge
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2021/02/23
Locating of the delayed activities
software process
stochastic Petri-nets
Markov random fields
metrics.
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