Feature selection by genetic algorithms in object-based classification of IKONOS imagery for forest mapping in Flanders, Belgium

2007 ◽  
Vol 110 (4) ◽  
pp. 476-487 ◽  
Author(s):  
F VANCOILLIE ◽  
L VERBEKE ◽  
R DEWULF
Keyword(s):  
Genetic Algorithms ◽  
Feature Selection ◽  
Forest Mapping ◽  
Object Based

Feature Selection via Genetic Algorithms in the Classification of Anti-Snake Venom Medicinal Plants

2010 ◽  
Vol 8 (3) ◽  
pp. 125-134
Author(s):  
Lariza L. de Oliveira ◽  
Gabriela F. Persinoti ◽  
Silvana Giuliatti ◽  
Renato Tinós
Keyword(s):  
Genetic Algorithms ◽  
Feature Selection ◽  
Medicinal Plants ◽  
Snake Venom

Genetic Algorithms for Feature Selection for Brain–Computer Interface

2015 ◽  
Vol 29 (05) ◽  
pp. 1559008 ◽  
Author(s):  
Izabela Rejer
Keyword(s):  
Genetic Algorithms ◽  
Feature Selection ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Eeg Signals ◽  
Crucial Problem ◽  
Left And Right ◽  
Selection For ◽  
First Time

The crucial problem that has to be solved when designing an effective brain–computer interface (BCI) is: how to reduce the huge space of features extracted from raw electroencephalography (EEG) signals. One of the strategies for feature selection that is often applied by BCI researchers is based on genetic algorithms (GAs). The two types of GAs that are most commonly used in BCI research are the classic algorithm and the Culling algorithm. This paper presents both algorithms and their application for selecting features crucial for the correct classification of EEG signals recorded during imagery movements of the left and right hand. The results returned by both algorithms are compared to those returned by an algorithm with aggressive mutation and an algorithm with melting individuals, both of which have been proposed by the author of this paper. While the aggressive mutation algorithm has been published previously, the melting individuals algorithm is presented here for the first time.

scholarly journals Object-Based vs. Pixel-Based Classification of Mangrove Forest Mapping in Vien An Dong Commune, Ngoc Hien District, Ca Mau Province Using VNREDSat-1 Images

2016 ◽  
Vol 05 (04) ◽  
pp. 284-295 ◽  
Author(s):  
Nguyen Thi Quynh Trang ◽  
Le Quang Toan ◽  
Tong Thi Huyen Ai ◽  
Nguyen Vu Giang ◽  
Pham Viet Hoa
Keyword(s):  
Mangrove Forest ◽  
Forest Mapping ◽  
Object Based
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