Before revision:  Contrary to previous deep learning methods, the proposed approach does not require any hand-crafted features while being faster and more parameter efficient.
After revision:  Contrary to previous deep learning methods, the proposed approach does not require any hand-crafted features or preprocessing. It improves on the state-of-the-art results while being more than two orders of magnitude faster and more parameter efficient.