INF 385T - Special Topics in Information Science: Crowdsourcing for Computer Vision

Spring 2017
Unique ID: 27997
Syllabus:   Syllabus
Prof:  Gurari, Danna
Room: UTA 1.210A
Days:  Wed
Time: 3:00 pm - 6:00 pm

Graduate standing. Additional prerequisites may vary with the topic.

Study of the properties and behavior of information. Technology for information processing and management.

Three lecture hours a week for one semester.

May be repeated for credit when the topics vary.

Topic Description:
Crowdsourcing for Computer Vision

Detailed Course Summary:
This class will cover fundamental and state-of-art problems in
computer vision, the sub-discipline of artificial intelligence
that tries to create computers that can "see". Students will
explore this field through examination of the human-based
challenges faced when teaching computers to see. Classes will be
a mix of lectures and hands-on training to develop practical
skills in web development and crowdsourcing. By the end of the
class, students will gain a basic understanding of machine
learning and a number of problems in computer vision.

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