Computational Geometry is about designing algorithms and data structures that reason about shape, position, and proximity — turning intuitive questions like "which points are closest?" or "do these polygons overlap?" into provably efficient procedures with real lower bounds. You'll work through four homework sets and a term project on top of a midterm and final, implementing and analyzing the canonical machinery — convex hulls, Voronoi diagrams, Delaunay triangulations, sweep-line intersection — rather than just reading about them. Building on your algorithms background, the course is the natural bridge to graphics, robotics, GIS, and CAD, where geometric correctness and efficiency stop being optional.
→ STARS müfredatı (resmi syllabus)
The use of GenAI tools such as ChatGPT as a supplementary resource in homework assignments or projects must be appropriately
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 Apply knowledge of mathematics MT HW Project Utilize and extend known algorithms, design paradigms and data structures for the solution of engineering problems MT HW Project Use modern software systems and tools Project