2024-06-29
24T2
00

Supervised learning for classification

  • Linear classification
  • Support vector machines
  • Multiclass classification
  • Classification performance evaluation

Supervised learning for regression

  • Linear regression
  • Least-squares regression
  • Regression performance evaluation
2024-06-29
24T2
00

Pattern recognition concepts

  • Definition and description of basic terminology
  • Recap of feature extraction and representation

Supervised learning for classification

  • Nearest class mean classification
  • K-nearest neighbours classification
  • Bayesian decision theory and classification
  • Decision trees for classification
  • Ensemble learning and random forests
2024-06-17
LEETCODE
00
2024-06-13
24T2
00

Shape features (Part 2)

  • Basic shape features
  • Shape context
  • Histogram of oriented gradients (HOG)
2024-06-13
24T2
00
  • Explain the need for feature representation

    Robustness, descriptiveness, efficiency

  • Discuss major categories of image features

    Colour features, texture features, shape features

  • Understand prominent feature descriptors

    Haralick features, local binary patterns, scale-invariant feature transform

  • Show examples of use in computer vision applications

    Image matching and stitching