Emanuel Indermühle

Artificial Intelligence · 2011–2012

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 6 citations into it; #30,136 of 35,345 by trust here, #31,361 by citations

Whom Emanuel Indermühle trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alex Graves
2. J. Urgen Schmidhuber
3. Volkmar Frinken
4. Geoffrey E. Hinton
5. Horst Bunke

Who trusts Emanuel Indermühle overall

1. J. Urgen Schmidhuber
2. Volkmar Frinken

Papers from Emanuel Indermühle's perspective

Ordered by how strongly the researchers Emanuel Indermühle trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Long Short-Term Memory
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. ImageNet: A large-scale hierarchical image database
8. Going deeper with convolutions
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Keyword Spotting in Online Handwritten Documents Containing Text and Non-text Using BLSTM Neural Networks (2011) — 11 citations
• Mode Detection in Online Handwritten Documents Using BLSTM Neural Networks (2012) — 43 citations