A. Mottaghi

Computer Vision and Pattern Recognition · 2021

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

Subfields

Whom A. Mottaghi trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)

Papers from A. Mottaghi's perspective

Ordered by how strongly the researchers A. Mottaghi 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: A large-scale hierarchical image database
  3. GENERATIVE ADVERSARIAL NETS
  4. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
  5. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  6. Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
  7. ImageNet classification with deep convolutional neural networks
  8. AutoAugment: Learning Augmentation Policies from Data
  9. Gradient-based learning applied to document recognition
  10. Detecting activities of daily living in first-person camera views

Their papers