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兰州大学 [53]
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期刊论文 [28]
会议论文 [25]
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专题:兰州大学
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Application of heterogeneous pulse coupled neural network in image quantization
期刊论文
Journal of Electronic Imaging, 2016, 卷号: 25, 期号: 6
作者:
Huang, Yi
;
Ma, Yide
;
Li, Shouliang
;
Zhan, Kun
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2017/01/16
Neural networks
Object recognition
Heterogeneous pulse
Human visual characteristics
Human Visual System
Image quantization
Natural images
Pulse coupled neural network models
Standard images
Synaptic connections
Computational Mechanisms of Pulse-Coupled Neural Networks: A Comprehensive Review
期刊论文
Archives of Computational Methods in Engineering, 2016, 页码: 1-16
作者:
Zhan, Kun
;
Shi, Jinhui
;
Wang, Haibo
;
Xie, Yuange
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2017/01/16
Image processing
Neural networks
Firing rates
Internal operations
Neuronal activities
Primary visual areas
Pulse coupled neural network
Time matrix
Visual image
A modified pulse-coupled spiking neuron circuit with memory threshold and its application
期刊论文
IEICE ELECTRONICS EXPRESS, 2016, 卷号: 13, 期号: 8
作者:
Ge, RJ
;
Zhang, L
;
Zhang, TF
;
Li, SL
;
Gui, G
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2017/01/16
modified pulsed-coupled spiking neurons circuit
chaos
image encryption
circuit implementation
Multi-focus Image Fusion Based on the Improved PCNN and Guided Filter
期刊论文
Neural Processing Letters, 2016, 页码: 1-20
作者:
Wang, Zhaobin
;
Wang, Shuai
;
Zhu, Ying
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  |  
浏览/下载:2/0
  |  
提交时间:2017/01/16
Image fusion
Bandpass filters
Neural networks
Guided filters
Human visual perception
Multifocus image fusion
Multifocus images
Objective evaluation criteria
PCNN
Pulse coupled neural network
Selection Rules
PCNN-based level set method of automatic mammographic image segmentation
期刊论文
OPTIK, 2016, 卷号: 127, 期号: 4, 页码: 1644-1650
作者:
Xie, WY
;
Li, YS
;
Ma, YD
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2017/01/16
Mammographic image
Image segmentation
Pulse coupled neural network
Level set method
Automated breast mass segmentation using pulse-coupled neural network and distance regularized level set evolution: A coarse-to-fine approach
会议论文
3rd International Conference on Bioimaging, BIOIMAGING 2016 - Part of 9th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2016, Rome, Italy, February 21, 2016 - February 23, 2016
作者:
Du, Songlin
;
Yan, Yaping
;
Ma, Yide
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2017/01/18
Image segmentation
Biomedical engineering
Computer aided diagnosis
Diseases
Neural networks
Numerical methods
Breast mass
Computer Aided Diagnosis(CAD)
Distance regularized level sets
Pulse coupled neural network
Quantitative experiments
Segmentation accuracy
Segmentation performance
The region of interest (ROI)
Region-Based Object Recognition by Color Segmentation Using a Simplified PCNN
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 卷号: 26, 期号: 8, 页码: 1682-1697
作者:
Chen, YL
;
Ma, YD
;
Kim, DH
;
Park, SK
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2017/01/16
Feature-based method
image segmentation
object recognition
region-based matching
simplified pulse-coupled neural network (SPCNN)
Review of Image Fusion Based on Pulse-Coupled Neural Network
期刊论文
Archives of Computational Methods in Engineering, 2015
作者:
Wang, Zhaobin
;
Wang, Shuai
;
Zhu, Ying
;
Ma, Yide
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2017/01/16
Image fusion
Neural networks
Existing problems
Image fusion techniques
Modified model
Pulse coupled neural network
Research development
MULTIFOCUS IMAGE FUSION BASED ON NONSUBSAMPLED CONTOURLET TRANSFORM AND SPIKING CORTICAL MODEL
期刊论文
NEURAL NETWORK WORLD, 2015, 卷号: 25, 期号: 6, 页码: 623-639
作者:
Wang, NY
;
Ma, YD
;
Wang, WL
;
Zhan, K
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2017/01/16
nonsubsampled contourlet transform (NSCT)
spiking cortical model (SCM)
multifocus image fusion
pulse coupled neural network (PCNN)
Mammalian visual characteristics inspired perceptual image quantization using pulse-coupled neural networks
期刊论文
OPTIK, 2015, 卷号: 126, 期号: 21, 页码: 3135-3139
作者:
Du, SL
;
Huang, Y
;
Ma, JL
;
Ma, YD
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2017/01/16
Image quantization
Mammalian visual characteristics (MVC)
Pulse-coupled neural network (PCNN)
Structural uncertainty
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