Much of the recent progress made in image classification research can be credited to training procedure refinements, such as changes in data augmentations and optimization methods.
#99 best model for Image Classification on ImageNet
It differs from the previous attention attempts in that, instead of using attention to blend hidden units of an encoder to a context vector at each decoder step, it uses attention as a pointer to select a member of the input sequence as the output.
Experiments show that human performance is well above current state-of-the-art baseline systems, leaving plenty of room for the community to make improvements.
DuConv enables a very challenging task as the model needs to both understand dialogue and plan over the given knowledge graph.
Konv enables a very challenging task as the model needs to both understand dialogue and plan over the given knowledge graph.
We show that an end-to-end deep learning approach can be used to recognize either English or Mandarin Chinese speech--two vastly different languages.
SOTA for Speech Recognition on WSJ eval93 (using extra training data)