Seung-Hwan Lim

Computer Vision and Pattern Recognition · 2015

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 Seung-Hwan Lim trusts overall

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

  1. Alex Krizhevsky
  2. James Bergstra

Papers from Seung-Hwan Lim's perspective

Ordered by how strongly the researchers Seung-Hwan Lim trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Learning Multiple Layers of Features from Tiny Images
  2. Practical Bayesian Optimization of Machine Learning Algorithms
  3. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  4. Caffe: Convolutional Architecture for Fast Feature Embedding
  5. ImageNet classification with deep convolutional neural networks
  6. Random Search for Hyper-Parameter Optimization
  7. Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
  8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  9. Gradient-based learning applied to document recognition
  10. Long Short-Term Memory

Their papers