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Investment of Classic Deep CNNs and SVM for Classifying Remote Sensing Images
Advances in Science, Technology and Engineering Systems
Feature extraction is an important process in image classification for achieving an efficient accuracy for the classification learning models. One of these methods is using the convolution neural networks. The use of the trained classic deep convolution neural networks as features extraction gives a considerable results in the remote sensing images classification models. So, this paper proposes three classification approaches using the support vector machine where based on the use of thedoi:10.25046/aj050580 fatcat:f477x2qcq5hjflfyobiimd6iji