Michael Bloesch

Computer Vision and Pattern Recognition · 2014–2018

A researcher in the Science corpus: 10 papers; trusts 248 researchers and is trusted by 47 researchers here, as inferred from the citation graph.

Subfields

Whom Michael Bloesch trusts overall

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

  1. Diederik P. Kingma
  2. Andrew J. Davison
  3. Jakob J. Engel
  4. Kaiming He
  5. Geoffrey E. Hinton
  6. Alex Krizhevsky
  7. Jimmy Ba
  8. Anastasios I. Mourikis
  9. Andreas Geiger
  10. Yoshua Bengio

Who trusts Michael Bloesch overall

  1. Guoquan Huang
  2. Antoni Rosinol
  3. Tong Qin
  4. Carlos Campos
  5. Ziwen Zhuang
  6. Zachary Teed
  7. Zipeng Fu
  8. Raul Mur-Artal
  9. Jeffrey A. Delmerico
  10. Jiawei Mo

Papers from Michael Bloesch's perspective

Ordered by how strongly the researchers Michael Bloesch 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 classification with deep convolutional neural networks
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. ImageNet: A large-scale hierarchical image database
  5. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Long Short-Term Memory
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers