EECE 7370 — Advanced Computer Vision
4 semester hoursGraduateLectureusually offered: falltypical days: TBostonSeattle, WATraditional
Offers students an opportunity to obtain practical knowledge in computer vision and to develop skills for being a successful researcher in this field. The goal of the field of computer vision is to make useful decisions about real physical objects and scenes based on sensed images. Achieving this goal requires obtaining and using descriptions (models) of the sensors and the world. Computer vision is an exciting field that builds on very diverse disciplines such as image processing, statistics, pattern recognition, control theory and system identification, physics, geometry, computer graphics, and machine learning. Course material includes state-of-the-art in the field, current research trends, and algorithms and their applications, with an emphasis on the mathematical methods used.
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Fall 2023 | 1 | 46 | 50 | 92% | 4.0 |
| Fall 2024 | 2 | 41 | 80 | 51% | 19.5 |
| Fall 2025 | 1 | 40 | 50 | 80% | 10.0 |
| Spring 2026 | 1 | 17 | 30 | 57% | 13.0 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 0% · T 100% · W 0% · Th 17% · F 0%
Common patterns: T (83% of sections), TR (17% of sections) — in patterns, R means Thursday
Professors
Fall
- Octavia Camps (94% of students) · reviews
- Joseph Weber (6% of students) · reviews
Spring
- Joseph Weber (100% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (EECE course descriptions) · Student reviews on RateMyHusky · All EECE courses · Plan it at numap.app