The literature is mostly image based, but as other users have said voice, text, and video have also seen substantial gains. It has also been used to great effect for taxi destination prediction (heterogenous information) [1], drug discovery [2], and general operations on graphs [3].

There are also lots of examples beyond classification - structured prediction such as image segmentation [4], predicting depth, surface normals, and pixels from only RGB [5], text to text translation [6], image captioning [7], Turing machines [8], speech synthesis [9], question answering (Q/A) [10][11], handwriting generation [12], playing Go [13], playing Atari [14], speech recognition [15], drawing things [16] and many more.

[1] http://blog.kaggle.com/2015/07/27/taxi-trajectory-winners-in...

[2] http://blog.kaggle.com/2012/11/01/deep-learning-how-i-did-it...

[3] http://arxiv.org/abs/1403.6652

[4] http://arxiv.org/abs/1502.03240

[5] http://arxiv.org/abs/1411.4734

[6] http://arxiv.org/abs/1409.0473

[7] http://arxiv.org/abs/1502.03044

[8] http://arxiv.org/abs/1410.5401

[9] http://arxiv.org/abs/1506.02216

[10] http://arxiv.org/abs/1507.04808

[11] http://arxiv.org/abs/1503.08895

[12] http://arxiv.org/abs/1308.0850

[13] http://arxiv.org/abs/1412.3409

[14] https://www.cs.toronto.edu/~vmnih/docs/dqn.pdf

[15] http://www.sciencedirect.com/science/article/pii/S0893608014...

[16] https://www.youtube.com/watch?v=Zt-7MI9eKEo