Standard syllabus
Computer vision · Graduate · CS / Programming
Topics
Imaging foundations
- Pinhole camera model and calibration (intro)
- Filtering, edge detection, and convolution
- Color spaces and histogram methods
- Feature descriptors: SIFT/HOG (survey)
- Stereo and depth from motion (intro)
Recognition pipelines
- Image classification with CNNs
- Object detection: R-CNN family survey
- Segmentation: semantic and instance (intro)
- Transfer learning and fine-tuning
- Data augmentation and dataset bias
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$1,162 · Computer vision · 18 tutoring hrs
Study guides, worksheets, reviews, practice tests, and answer keys for 1 class. 18 tutoring hours (1 hr / week · semester). Bundle discount applied vs buying separately. Pay in full via Zelle.