throws away over 68% of the input image when predict-ing the class scores, losing much of the spatial context. Therandom cropping model achieved a validation accuracy of70.04% after 400,200 SGD iterations. In comparison, thefully convolutional model achieved 71.58% validation accu-racy after only 223,500 iterations. Both models were trainedin roughly three days. Despite reinitializing the ﬁnal convo-lutional layers from scratch, the fully convolutional modelexhibits faster learning and better performance. The ﬁnalfully convolutional model achieves a validation accuracy of71.71%, trained over 345,000 iterations.