• Aucun résultat trouvé

Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review.

N/A
N/A
Protected

Academic year: 2021

Partager "Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review."

Copied!
21
0
0

Texte intégral

Loading

Figure

Table  I  summarizes  the  review  papers  on  recent  classification algorithms of remote sensing data, where a large  part  of  the  literature  is  devoted  to  RFs  or  is  discussed  as  an  alternative  classifier
TABLE I. S UMMARY OF RELATED SURVEYS ON REMOTE SENSING IMAGE CLASSIFICATION  ( THE NUMBER OF CITATIONS IS REPORTED BY  A PRIL  20, 2020)
Fig. 3.  An SVM example for linearly separable data.
Fig. 5.  The widely used ensemble learning methods: (a) Boosting and (b) Bagging.
+7

Références

Documents relatifs

definition of vulnerability we use, they cannot logically modify the associations between heat and mortality... In addition, the reference sections of studies identified as

Specifically, we calcu- lated unadjusted repeatability (R), repeatability adjusted for test order (R n ), and repeatability adjusted for test order and individ- ual determinants (R ni

Studies show that adverse changes in retinal vascular caliber (principally narrower retinal arteriolar caliber and wider venular caliber) are associated with cardiovascular

Quinolones versus macrolides in the treatment of legionellosis: a systematic review and meta-analysis.. Charles Burdet, Raphaël Lepeule, Xavier Duval, Marion Caseris, Christophe

Study Location Period Study Design Congenital Categories Exposure Assessment Exposure Variable Air Pollutants Results Confounders.. Gianicolo

Dans les entreprises de 10 salariés ou plus de l’ensemble de l’économie hors agriculture et hors emplois publics, 84,3 % des salariés travaillent à temps complet au

Lanham-New 1 1 Nutritional Sciences Division, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, 2 Centre for Health Economics, University of York,

The second part is a meta-analysis of the effectiveness of gamification (assessed through RCT studies) applied to cognitive training with the following objectives: (1) assess