Conclusion 

• The performance of the two classifiers, namely, WVIMDC and WVINN has been compared for identifying defects on plywood.

• The results show that the efficiency of the WVINN is higher than that of the WVIMDC.

• This shows that the neural network behaves like a non-linear machine by having more than one layer of weights, and can be trained to learn the non-linear discriminating functions between the different classes.