×
验证码:
换一张
忘记密码?
记住我
CORC
首页
科研机构
检索
知识图谱
申请加入
托管服务
登录
注册
在结果中检索
科研机构
兰州理工大学 [1]
长春光学精密机械与物... [1]
自动化研究所 [1]
重庆绿色智能技术研究... [1]
内容类型
会议论文 [4]
发表日期
2021 [1]
2013 [1]
2012 [1]
2011 [1]
×
知识图谱
CORC
开始提交
已提交作品
待认领作品
已认领作品
未提交全文
收藏管理
QQ客服
官方微博
反馈留言
浏览/检索结果:
共4条,第1-4条
帮助
限定条件
内容类型:会议论文
已选(
0
)
清除
条数/页:
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
排序方式:
请选择
作者升序
作者降序
题名升序
题名降序
发表日期升序
发表日期降序
提交时间升序
提交时间降序
Proxy Graph Matching with Proximal Matching Networks
会议论文
线上远程会议, 2021-2-7
作者:
Tan HR(檀昊儒)
;
Wang C(王闯)
;
Wu ST(吴思彤)
;
Wang TQ(王铁强)
;
Zhang XY(张煦尧)
收藏
  |  
浏览/下载:41/0
  |  
提交时间:2021/07/01
Graph Matching
Combinatorial Optimization
Deep Learning
Research on receiver autonomous integrity monitoring algorithm using genetic algorithm resampling particle filter
会议论文
Wuhan, China, May 13, 2013 - May 17, 2013
作者:
He, Pan
;
Tan, Chun
;
Huang, Huawen
收藏
  |  
浏览/下载:14/0
  |  
提交时间:2018/03/16
Image matching using a bat algorithm with mutation (EI CONFERENCE)
会议论文
2012 International Conference on Mechatronic Systems and Automation Systems, MSAS 2012, July 21, 2012 - July 21, 2012, Wuhan, China
Zhang J.
;
Wang G.
收藏
  |  
浏览/下载:29/0
  |  
提交时间:2013/03/25
Due to shortcoming of traditional image matching for computing the fitness for every pixel in the searching space
a new bat algorithm with mutation (BAM) is proposed to solve image matching problem
and a modification is applied to mutate between bats during the process of the new solutions updating. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for this improved meta-heuristic approach BAM is also presented. To prove the performance of this proposed meta-heuristic method
BAM is compared with BA and other population-based optimization methods
DE and SGA. The experiment shows that the proposed approach is more effective and feasible in image matching than the other model. (2012) Trans Tech Publications
Switzerland.
Bionic optimization algorithm based on the MMAS and the artificial fish
会议论文
作者:
Xin, Feng
;
Ming, Wang Xiao
;
Wu, Dang Jian
收藏
  |  
浏览/下载:0/0
  |  
提交时间:2020/11/15
Ant colony optimization
Bionics
Global optimization
Ant colony algorithms
Artificial fish algorithms
Bionic optimization
Crowded degree
Local extreme values
MMAS
Premature stagnation phenomenon
visual
©版权所有 ©2017 CSpace - Powered by
CSpace