Hooman Parvardeh

Computer Vision and Pattern Recognition · 2016

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Hooman Parvardeh trusts

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

  1. David G. Lowe (in Computer Vision and Pattern Recognition)
  2. Matthijs C. Dorst (in Computer Vision and Pattern Recognition)
  3. Pedro M. Domingos (in Artificial Intelligence)

Papers from Hooman Parvardeh's perspective

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

  1. Object recognition from local scale-invariant features
  2. The Laplacian Pyramid as a Compact Image Code
  3. Experiments with a New Boosting Algorithm
  4. Random Forests
  5. Support-Vector Networks
  6. Bundle Adjustment in the Large (European Conference on Computer Vision)
  7. The WEKA data mining software: an update
  8. Distinctive Image Features from Scale-Invariant Keypoints Abstract by Matthijs Dorst Based on the paper by
  9. Local Laplacian filters: edge-aware image processing with a Laplacian pyramid (ACM Transactions on Graphics)
  10. An Algorithm for Least-Squares Estimation of Nonlinear Parameters

Their papers