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Image understanding as a second course in AI: preparing students for research

Published: 03 March 2006 Publication History

Abstract

This paper describes the development and structure of a second course in artificial intelligence that was developed to meet the needs of upper-division undergraduate and graduate computer science and computer engineering students. These students already have a background in either computer vision or artificial intelligence, and desire to apply that knowledge to the design of algorithms that are able to automate the process of extracting semantic content from either static or dynamic imagery. Theory and methodology from diverse areas were incorporated into the course, including techniques from image processing, statistical pattern recognition, knowledge representation, multivariate analysis, cognitive modeling, and probabilistic inference. Students read selected current literature from the field, took turns presenting the selected literature to the class, and participated in discussions about the literature. Programming projects were required of all students, and in addition, graduate students were required to propose, design, implement, and defend an image understanding project of their own choosing. The course served as preparation for and an incubator of an active research group.

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Cited By

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  • (2017)Analysis of student characteristics and feeling of efficacy in a first undergraduate artificial intelligence course2017 IEEE International Conference on Electro Information Technology (EIT)10.1109/EIT.2017.8053322(010-015)Online publication date: May-2017
  • (2010)Shape matching through contour extraction using Circular Augmented Rotational Trajectory (CART) algorithmInternational Journal of Business Intelligence and Data Mining10.1504/IJBIDM.2010.0312875:2(192-210)Online publication date: 1-Jan-2010

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  1. Image understanding as a second course in AI: preparing students for research

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    Published In

    cover image ACM SIGCSE Bulletin
    ACM SIGCSE Bulletin  Volume 38, Issue 1
    March 2006
    553 pages
    ISSN:0097-8418
    DOI:10.1145/1124706
    Issue’s Table of Contents
    • cover image ACM Conferences
      SIGCSE '06: Proceedings of the 37th SIGCSE technical symposium on Computer science education
      March 2006
      612 pages
      ISBN:1595932593
      DOI:10.1145/1121341
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 03 March 2006
    Published in SIGCSE Volume 38, Issue 1

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    Author Tags

    1. artificial intelligence education
    2. computer vision
    3. course design
    4. student projects

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    • (2017)Analysis of student characteristics and feeling of efficacy in a first undergraduate artificial intelligence course2017 IEEE International Conference on Electro Information Technology (EIT)10.1109/EIT.2017.8053322(010-015)Online publication date: May-2017
    • (2010)Shape matching through contour extraction using Circular Augmented Rotational Trajectory (CART) algorithmInternational Journal of Business Intelligence and Data Mining10.1504/IJBIDM.2010.0312875:2(192-210)Online publication date: 1-Jan-2010

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