Daniel J. Mollura

Computer Vision and Pattern Recognition · 2014–2016

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Daniel J. Mollura trusts

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

  1. Alex Krizhevsky (in Computer Vision and Pattern Recognition)
  2. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  3. Rob Fergus (in Computer Vision and Pattern Recognition)
  4. Karen Simonyan (in Computer Vision and Pattern Recognition)
  5. Geoffrey E. Hinton (in Computer Vision and Pattern Recognition)
  6. David G. Lowe (in Computer Vision and Pattern Recognition)
  7. Ross B. Girshick (in Computer Vision and Pattern Recognition)
  8. Jitendra Malik (in Computer Vision and Pattern Recognition)
  9. Ilya Sutskever (in Computer Vision and Pattern Recognition)
  10. Yann LeCun (in Computer Vision and Pattern Recognition)

Who trusts Daniel J. Mollura

  1. Chaopeng Shen (in Radiology, Nuclear Medicine and Imaging)
  2. Mohammad Mustafa Taye (in Computer Vision and Pattern Recognition)

Papers from Daniel J. Mollura's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Gradient-based learning applied to document recognition
  3. Learning Multiple Layers of Features from Tiny Images
  4. Going deeper with convolutions
  5. ImageNet: A large-scale hierarchical image database
  6. Distinctive Image Features from Scale-Invariant Keypoints
  7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  8. Fully convolutional networks for semantic segmentation
  9. Visualizing and Understanding Convolutional Networks
  10. CNN Features Off-the-Shelf: An Astounding Baseline for Recognition

Their papers