Course Identification

Advanced Topics in Computer Vision and Deep Learning
20244042

Lecturers and Teaching Assistants

Prof. Michal Irani, Prof. Tali Dekel, Dr. Mark Sheinin, Prof. Shimon Ullman, Dr. Shai Bagon
Kateryna Yurkova, Navve Wasserman

Course Schedule and Location

2024
Second Semester
Tuesday, 10:15 - 12:00, Ziskind, Rm 1
09/04/2024
09/07/2024

Field of Study, Course Type and Credit Points

Mathematics and Computer Science: Seminar; Elective; Regular; 2.00 points
Chemical Sciences: Lecture; 2.00 points
Life Sciences: Lecture; 2.00 points
Life Sciences (Brain Sciences: Systems, Computational and Cognitive Neuroscience Track): Lecture; 2.00 points

Comments

Advanced Reading-Group Seminar.
Absence from lessons must be for a justified reason, and with prior approval.
Priority will be given to students from the Math and CS faculty.

















Prerequisites

Both these courses are mandatory prerequisites:

  • Introduction to computer vision.
  • Deep Learning for Computer Vision: Fundamentals and Applications.

Unless the student took an equivalent course in another university, in which case they will have to point to the specific course they took.

 

Restrictions

24

Language of Instruction

English

Attendance and participation

Obligatory

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)

10%
5%
85%
The grade is based on a presentation, attendance, and reading papers

Evaluation Type

Seminar

Scheduled date 1

N/A
N/A
-
N/A

Estimated Weekly Independent Workload (in hours)

3

Syllabus

This course will cover important advances and recently published papers in Computer Vision and Deep Learning.

Learning Outcomes

Upon successful completion of this course students should be able to:

Become familiar with advances and recently published papers in the area of Deep Learning and applications to Computer Vision. In addition, an emphasis will be put on how to prepare a good presentation.

Reading List

List of papers to read will be given at the beginning of the course.

Website

N/A