ADAN 7399 Computer Vision
This course introduces students to computer vision concepts and methods. Students will learn how to conduct classification, detection, and recognition tasks. The course covers 1) the basics of computer vision, 2) machine learning (ML) models for vision, 3) Convolutional Neural Networks (CNN) and transformer architecture, 4) object detection and image segmentation, 5) autoencoders & image manipulation, 6) Generative Adversarial Networks for image creation, and 7) multi-input models.
Course overview
- Department
- Advancing Studies
- School
- ADV
- Credits
- 3
- Level
- Graduate
- Offered
- Periodically
Catalog details
Course evaluations
- Course rating
- 4.55 / 5 · Excellent
- Instructor rating
- 4.78 / 5 · Excellent
- Terms evaluated
- 4
| Term | Instructor | Course overall | Instructor overall | Well organized | Clear learning objectives | Intellectually challenging | Helpful assignments | Applicable beyond course | Attendance necessary | Weekly effort | Responses |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Spring 2025 | Lawrence Fulton | 4.3 | 4.7 | 5.0 | 5.0 | 5.0 | 4.7 | 5.0 | 4.3 | 10+ hrs/week | 3 of 5 |
| Fall 2024 | Lawrence Fulton | 4.7 | 4.7 | 4.7 | 4.7 | 4.9 | 4.7 | 4.7 | 4.2 | 10+ hrs/week | 7 of 8 |
| Spring 2024 | Lawrence Fulton | 4.8 | 5.0 | 4.8 | 4.8 | 4.8 | 4.8 | 4.8 | 4.3 | 4–6 hrs/week | 6 of 11 |
| Fall 2023 | Lawrence Fulton | 3.5 | 4.5 | 3.5 | 4.5 | 4.5 | 4.0 | 4.5 | 3.5 | — | 2 of 6 |