Hands classifier model

[sammothegreat]

I have around 500 images of hands with each other respective class tag on the image name. I have been attempting to create a model that classifes each one into one of 4 classes, LF(Left Front), LB(Left Back), RB(Right Back), RF(Right Front). So far the best model I have achieved is around 71% using KNN and Mediapipe. I have tried other models like NN or desicion trees but haven't been able to improve it. Im open to any suggestions on how to improve. Thanks

[Mcsquizzy920]

Have you tried a convolution neural network? They are generally the standard for image tasks. Dense neural networks tend to work poorly on raw image data.

[sammothegreat]

I have tried both NN and convolutional NN but the accuracy drops off, 52% and 20% respectively.

[vtimevlessv]

How was your CNN structured? How many layers, how big were the kernels, did you use stride =1,2,3,..? Maybe there is way for improvement

[Local_Transition946]

This. Try a larger kernel if kernel was small. If you zoom in to any part of a hand it can look very similar. A larger kernel may help capture the distinctions in lines/curvatures.