Monika Bansal

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Monika Bansal trusts overall

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

  1. David G. Lowe
  2. Tianqi Chen
  3. Samir S. Yadav
  4. Herbert Bay
  5. Ethan Rublee
  6. Carlos Guestrin
  7. Shivajirao Manikrao Jadhav
  8. Tinne Tuytelaars
  9. Vincent Rabaud
  10. Jianbo Shi

Papers from Monika Bansal's perspective

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

  1. Distinctive Image Features from Scale-Invariant Keypoints
  2. ImageNet classification with deep convolutional neural networks
  3. Gradient-based learning applied to document recognition
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. ImageNet: A large-scale hierarchical image database
  6. ImageNet Large Scale Visual Recognition Challenge
  7. Going deeper with convolutions
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Long Short-Term Memory

Their papers