Kingshy Goh

Computer Vision and Pattern Recognition · 2003

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Kingshy Goh trusts overall

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

  1. Vladimir Naumovich Vapni
  2. Kobus Barnard
  3. Simon Tong
  4. Charu C. Aggarwal
  5. Robert E. Schapire
  6. Erin L. Allwein
  7. James Ze Wang

Who trusts Kingshy Goh overall

  1. Yong Wang

Papers from Kingshy Goh's perspective

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

  1. The Nature of Statistical Learning Theory
  2. Support-Vector Networks
  3. Transductive Inference for Text Classification using Support Vector Machines
  4. Statistical Learning Theory
  5. Learning the semantics of words and pictures
  6. SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries (IEEE Transactions on Pattern Analysis and Machine Intelligence)
  7. Boosting the margin: A new explanation for the effectiveness of voting methods
  8. Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers
  9. A Tutorial on Support Vector Machines for Pattern Recognition
  10. Textural Features Corresponding to Visual Perception

Their papers