Tomoaki Nishimura

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Tomoaki Nishimura trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  2. Karen Simonyan (in Computer Vision and Pattern Recognition)
  3. Francis R. Bach (in Artificial Intelligence)

Papers from Tomoaki Nishimura's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet: A large-scale hierarchical image database
  3. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. Rectified Linear Units Improve Restricted Boltzmann Machines
  5. Densely Connected Convolutional Networks
  6. Network In Network
  7. Regularization of Neural Networks using DropConnect
  8. Deep Sparse Rectifier Neural Networks
  9. Rectifier Nonlinearities Improve Neural Network Acoustic Models
  10. Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation

Their papers