CS 585 is about getting deep networks to *produce* images and video rather than just classify them — learning the distribution of pixels well enough to synthesize, translate, inpaint, or extend them. Most of the weight sits on a semester-long project plus a presentation and report, with a midterm and final framing the theory behind GANs, transformers, and self-supervised reconstruction. It assumes you're comfortable with CNNs and basic deep learning from CS 464/484, and it's the natural follow-up if you want to do research in vision, multimodal models, or anything generative downstream.
→ STARS müfredatı (resmi syllabus)
İlk dosyayı sen atarsan — not, slayt, geçmiş sınav, çözüm, cheat-sheet, ne varsa — defter ekibi öğrenci paylaşımlarından bu dersin notlarını yazar. Drive linki / PDF / ZIP, hepsi olur.
Course Learning Outcomes: Course Learning Outcome Assessment