Cohen, Ira
Machine Learning in Computer Vision
1. Introduction
2. Theory: Probabilistic Classifiers
3. Theory: Generalization Bounds
4. Theory: Semi-Supervised Learning
5. Algorithm: Maximum Likelihood Minimum Entropy HMM
6. Algorithm: Margin Distribution Optimization
7. Algorithm: Learning the Structure of Bayesian Network Classifiers
8. Application: Office Activity Recognition
9. Application: Multimodal Event Detection
10. Application: Facial Expression Recognition
11. Application: Bayesian Network Classifiers for Face Detection
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Avainsanat: COMPUTERS / Computer Science COM014000
- Tekijä(t)
- Cohen, Ira
- Garg, Ashutosh
- Huang, Thomas S.
- Sebe, N.
- Julkaisija
- Springer
- Julkaisuvuosi
- 2005
- Kieli
- en
- Painos
- 1
- Kategoria
- Tietotekniikka, tietoliikenne
- Tiedostomuoto
- E-kirja
- eISBN (PDF)
- 9781402032752