This project is Example of Binary image Classifiers using CNN model. In this one we are comparing Gold and coppers images and it will give distingiush between gold and copper.
Some of the results are mentioned below:
Train on 921 samples, validate on 103 samples Epoch 1/10 921/921 [==============================] - 3s 3ms/sample - loss: 0.3759 - acc: 0.8360 - val_loss: 0.3590 - val_acc: 0.9223 Epoch 2/10 921/921 [==============================] - 1s 1ms/sample - loss: 0.2549 - acc: 0.9121 - val_loss: 0.2829 - val_acc: 0.9417 Epoch 3/10 921/921 [==============================] - 1s 1ms/sample - loss: 0.1430 - acc: 0.9468 - val_loss: 0.1320 - val_acc: 0.9612 Epoch 4/10 921/921 [==============================] - 1s 999us/sample - loss: 0.0747 - acc: 0.9707 - val_loss: 0.1106 - val_acc: 0.9612 Epoch 5/10 921/921 [==============================] - 1s 1ms/sample - loss: 0.0518 - acc: 0.9815 - val_loss: 0.2039 - val_acc: 0.9223 Epoch 6/10 921/921 [==============================] - 1s 1ms/sample - loss: 0.0571 - acc: 0.9772 - val_loss: 0.1507 - val_acc: 0.9515 Epoch 7/10 921/921 [==============================] - 1s 995us/sample - loss: 0.0307 - acc: 0.9891 - val_loss: 0.1775 - val_acc: 0.9320 Epoch 8/10 921/921 [==============================] - 1s 992us/sample - loss: 0.0277 - acc: 0.9924 - val_loss: 0.1874 - val_acc: 0.9515 Epoch 9/10 921/921 [==============================] - 1s 989us/sample - loss: 0.0131 - acc: 0.9967 - val_loss: 0.2154 - val_acc: 0.9612 Epoch 10/10 921/921 [==============================] - 1s 993us/sample - loss: 0.0116 - acc: 0.9967 - val_loss: 0.2356 - val_acc: 0.9417