Published July 27, 2017 | Version v1
Figure Open

RAIN Journal-ANNSVM: A Novel Method for Graph-Type Classification by Utilization of Fourier Transformation, Wavelet Transformation, and Hough Transformation-Figure 4. Processes of all experiments:

  • 1. Graduate School, Shibaura Institute of Technology, Tokyo, Japan
  • 2. Information Science and Engineering, Shibaura Institute of Technology, Tokyo, Japan

Description

In this study, accuracy values of each dataset showed the performance of each method. These values represent are the proportion of the total number of predictions that were correctly classified. Initially, we classified training instances into three classes, with approximately 300 images per class. The graphs had been selectively gathered from the Web. We manually normalized the collected images by eliminating unused areas, such as unnecessary text. Moreover, we evaluated the experiments with 10 folds cross-validation because such an approach can mitigate the problem of over-fitting. 

Notes

https://www.edusoft.ro/brain/index.php/brain/article/view/685/763

Files

Figure 4. Processes of all experiments.JPG

Files (44.4 kB)

Name Size Download all
md5:8ea72c53e78fc534c67e978bda795b5a
44.4 kB Preview Download