Muntaqim Mehtaz

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Muntaqim Mehtaz trusts overall

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

  1. Geoffrey E. Hinton
  2. Kaiming He
  3. Diederik P. Kingma

Papers from Muntaqim Mehtaz's perspective

Ordered by how strongly the researchers Muntaqim Mehtaz 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. Going deeper with convolutions
  4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  6. ImageNet classification with deep convolutional neural networks
  7. Microsoft COCO: Common Objects in Context
  8. Fully convolutional networks for semantic segmentation
  9. Rectified Linear Units Improve Restricted Boltzmann Machines
  10. Gradient-based learning applied to document recognition

Their papers