A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is
The Target Classification of Optical Remote Sensing Image Based on Hierarchical Features and AdaBoost Algorithm
International Journal of Signal Processing, Image Processing and Pattern Recognition
In order to accurately classify and recognize specific targets in remote sensing images, a novel recognition method based on hierarchical features and AdaBoost algorithm is proposed. Hierarchical features can represent the distribution characteristics of targets effectively by applying the image pyramid idea to the BoF-SIFT feature extraction. The AdaBoost algorithm with support vector machine(SVM) as the weak classifiers is used for targets classification. The proposed classification anddoi:10.14257/ijsip.2017.10.1.03 fatcat:uqntimy5n5gqdj7giipad6hkky