CMSC848B
Selected Topics in Information Processing; Computational Imaging
Prerequisite: Familiarity with linear algebra and python or matlab is required. Familiarity with deep learning and statistics is a plus. Introduce various computational imaging systems and the algorithms that underlie their operation. Particular emphasis will be placed on recently developed learning based reconstruction algorithms.
Sister Courses: CMSC848C, CMSC848D, CMSC848E, CMSC848F, CMSC848G, CMSC848I, CMSC848J, CMSC848K, CMSC848M, CMSC848N, CMSC848O, CMSC848P, CMSC848Q, CMSC848R, CMSC848T, CMSC848U, CMSC848W, CMSC848Z
Fall 2025
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During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.
Average GPA of 3.73 between 96 students*
* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.