Figure 6.

Ensemble architecture: integrating the multinomial logistic regression (MLR), decision tree classifier (DTC), and convolutional neural network (CNN) learners, where the handcrafted features $X_{min},X_{min}Y,X_{max},X_{max}Y,Y_{min}X,Y_{min},Y_{max}X,Y_{max}$ and images are used as inputs. The outputs $y_{1i}..$$y_{5k}$ are the predictions of each product cut from the MLR, DTC, and CNN algorithms, which are then fed to a standard Neural Network (NN), whose outputs correspond to prediction of product cuts 20001, 20002, 20003, 20004, and 20010.