I am working on the comparison of Histogram of oriented gradient (HoG) and Convolutional Neural Network (CNN) for the weed detection. I have two datasets of two different weeds.
CNN architecture is 3 layer network.
Using the CNN I am getting a testing accuracy of 77% and for HoG with SVM 78%.
For this dataset, using CNN I am getting a test accuracy of 94% and for HoG with SVM 60%.
My question is Why I am getting higher accuracy for HoG using first dataset? CNN should be much better than HoG.
The only reason comes to my mind is the first data has only 18 images and less diverse as compare to the 2nd dataset. is it correct?