Lectures
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| Weeks; | Lecture Topics and Important Events |
|---|---|
| 1 | Cepstrum and speech production | .
| 2 | Speech perception, MFCC, and MP1 walkthrough |
| 3 | PCA applications to face detection and recognition MP1 due, MP2 walkthrough |
| 4 | Probability basics, Bayesian decision rule, Max-likelihood; Speaker identification |
| 5 |
Bayesian Networks (BN) and EM algorithm MP2 due, MP3 walkthrough |
| 6 |
EM algorithm cont'd Exam 1 |
| 7 |
Hidden Markov Models (HMM) MP3 due, MP4 walkthrough |
| 8 | Audio/visual speech recognition |
| 9 |
3D face modeling, analysis, and animation; MPEG 4 MP4 due, MP5 walkthrough |
| 10 | Spring Break |
| 11 |
Image features, segmentation
Exam 2 |
| 12 |
Adaboost and object detection, MP5 due |
| 13 |
Adaboost and object detection.
|
| 14 |
Neural nets and MP7c
walkthrough Reading: Backpropagation |
| 15 | Mahalanobis distance, metric learning, boundary detection Reading: Mahalanobis distance, Shot transition detection |
| 16 | MP7 due Exam 3 Review |
| 17 | Exam 3 |