Before revision:  We use transfer learning to extract visual semantics  as concepts, scenes, and objects, which allows us to interpret and explain the trained model and predictions.
After revision:  We use transfer learning to extract visual semantics such as concepts, scenes, and objects, which allows us to interpret and explain the trained model and predictions.