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Deep-Sceen-Classification

version 1.0.0 (38 MB) by muhammet balcilar
Comparison of Sceen Classification accuracy between Histogram, SIFT and Deep Learning based features

159 Downloads

Updated 31 Jul 2018

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Scene classification with using some certain different images of scenes are very important and crucial issue in computer vision literature. Especially, to automatize it with computer has significant amount of benefit in terms of robotic and automation. Although computers are still far from the human beings ability in order to visual understanding, the researchers have done too many significant contribution on this area. As general classification problem, image scene classification problem has the same two fundamental step in it. These are feature extraction and classification respectively. In this research, we have focused on three different image features which are histogram of color, bag of sift features and finally convolution neural networks. For classification method, we have just tried multi class support vector machine. Our research shows that pretrained convolutional neural network named vgg16 has reasonable accuracy.

Cite As

muhammet balcilar (2021). Deep-Sceen-Classification (https://github.com/balcilar/Deep-Scene-Classification), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2018a
Compatible with any release
Platform Compatibility
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vlfeat-0.9.21/apps

vlfeat-0.9.21/apps/recognition

vlfeat-0.9.21/toolbox

vlfeat-0.9.21/toolbox/aib

vlfeat-0.9.21/toolbox/demo

vlfeat-0.9.21/toolbox/fisher

vlfeat-0.9.21/toolbox/geometry

vlfeat-0.9.21/toolbox/gmm

vlfeat-0.9.21/toolbox/imop

vlfeat-0.9.21/toolbox/kmeans

vlfeat-0.9.21/toolbox/misc

vlfeat-0.9.21/toolbox/mser

vlfeat-0.9.21/toolbox/plotop

vlfeat-0.9.21/toolbox/quickshift

vlfeat-0.9.21/toolbox/sift

vlfeat-0.9.21/toolbox/slic

vlfeat-0.9.21/toolbox/special

vlfeat-0.9.21/toolbox/vlad

vlfeat-0.9.21/toolbox/xtest

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.