2022
DOI: 10.1007/978-981-19-4109-2_27
|View full text |Cite
|
Sign up to set email alerts
|

A New High-Dimensional Particle Swarm Evolution Algorithm Based on New Fitness Allocation and Multi-criteria Strategy

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2023
2023
2023
2023

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 21 publications
0
1
0
Order By: Relevance
“…The RANSAC algorithm is used to estimate a better data model applicable to the dataset by repeatedly selecting a random sample set. The results processed by the RANSAC algorithm are shown in Figure 4 The size of the singleresponse matrix required for splicing is 3 × 3 and contains 8 unknowns [13] , and to solve it, at least 8 linear equation sets are required, and 8 linear equation sets are needed to find 4 matching point pairs in the two images. The single-response matrix is calculated as:…”
Section: Improved Ransac Algorithmmentioning
confidence: 99%
“…The RANSAC algorithm is used to estimate a better data model applicable to the dataset by repeatedly selecting a random sample set. The results processed by the RANSAC algorithm are shown in Figure 4 The size of the singleresponse matrix required for splicing is 3 × 3 and contains 8 unknowns [13] , and to solve it, at least 8 linear equation sets are required, and 8 linear equation sets are needed to find 4 matching point pairs in the two images. The single-response matrix is calculated as:…”
Section: Improved Ransac Algorithmmentioning
confidence: 99%