Abbas Cheddad

Computer Vision and Pattern Recognition · 2010–2019

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Abbas Cheddad trusts overall

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

  1. Niels Provos
  2. Jessica J. Fridrich
  3. Phil Sallee
  4. Tomás Pevný
  5. Peter Honeyman
  6. Pierre Moulin
  7. Piyu Tsai
  8. Miroslav Goljan
  9. Yann LeCun
  10. Ralf Koetter

Papers from Abbas Cheddad's perspective

Ordered by how strongly the researchers Abbas Cheddad 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. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Going deeper with convolutions
  6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  7. Learning Multiple Layers of Features from Tiny Images
  8. ImageNet Large Scale Visual Recognition Challenge
  9. Long Short-Term Memory
  10. ImageNet: A large-scale hierarchical image database

Their papers