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Weuse the twohighest frequencyones which result in 776 label categories. Thelearningrateis12 decreased by afactor of 10 atthe end of 10th and 20th epochs. The networks are trained for 36epochs. Since the all the labels for the test images are not annotated, we only evaluate the performance of17 our model on the set of annotated labels. Hence false positive can happen only if apositively18 annotated label is predicted as a negative class.