2014
DOI: 10.3103/s0278641914020101
|View full text |Cite
|
Sign up to set email alerts
|

Estimating the convergence of a simulated annealing algorithm for the problem of constructing multiprocessor schedules

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2015
2015
2018
2018

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 1 publication
0
1
0
Order By: Relevance
“…Digital image security appraisal in recent years become emerging in the field of information security and extremely important research topic, also is the key technology of image content security. Research institutions and scholars at home and abroad for the passive security appraisal of the research work focus on two aspects: on the one hand, is based on single feature in the tamper with the changes before and after testing the method advantage is don't need a photo gallery of training classifier, directly on the image authenticity verification, but has its limitations, the detection accuracy is low [6][7][8]. On the other hand is based on image feature elements more analysis of the detection, identification testing methods of the class is mainly by extracting the image to be detected a variety of statistical features and combination, the final decision is obtained by classifier to classify the method need gallery training classifier, increase the complexity of computation, but its detection accuracy is higher.…”
Section: Introductionmentioning
confidence: 99%
“…Digital image security appraisal in recent years become emerging in the field of information security and extremely important research topic, also is the key technology of image content security. Research institutions and scholars at home and abroad for the passive security appraisal of the research work focus on two aspects: on the one hand, is based on single feature in the tamper with the changes before and after testing the method advantage is don't need a photo gallery of training classifier, directly on the image authenticity verification, but has its limitations, the detection accuracy is low [6][7][8]. On the other hand is based on image feature elements more analysis of the detection, identification testing methods of the class is mainly by extracting the image to be detected a variety of statistical features and combination, the final decision is obtained by classifier to classify the method need gallery training classifier, increase the complexity of computation, but its detection accuracy is higher.…”
Section: Introductionmentioning
confidence: 99%