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Sketch Recognition Algorithms: Analysis, Implementation, and Comparison using AI Techniques

This lecture explores various sketch recognition algorithms, including feature-based, vision-based, geometry-based, and timing-based approaches. It also covers methods to combine results from different algorithms to improve recognition using AI techniques. Learn how to bring your drawings to life!

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Sketch Recognition Algorithms: Analysis, Implementation, and Comparison using AI Techniques

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  1. Lecture 4: SKETCH RECOGNITION Analysis, implementation, and comparison of sketch recognition algorithms, including feature-based, vision-based, geometry-based, and timing-based recognition algorithms; examination of methods to combine results from various algorithms to improve recognition using AI techniques, such as graphical models. Learn how to make your drawings come alive…

  2. Class Overview • Long Paper discussion (lead by ?) • Brief Lecture on Long • Discussion of previous homework and implementation issues • MARQS: Presentation and Discussion • Homework

  3. Long Paper Discussion: (lead by ?) • Thoughts?

  4. Class Overview • Long Paper discussion (lead by ?) • Brief Lecture on Long • Discussion of previous homework and implementation issues • MARQS: Presentation and Discussion • Homework

  5. Class Overview • Long Paper discussion (lead by ?) • Brief Lecture on Long • Discussion of previous homework and implementation issues • MARQS: Presentation and Discussion • Homework

  6. Homework Implementation Discussion • Compare recognition results. • What did people get? • Implementation difficulties?

  7. Performing Recognition on these Features • What do you think about the features? • What recognition problems did you have? • Can you think of better features? (this is your homework)

  8. Class Overview • Long Paper discussion (lead by ?) • Brief Lecture on Long • Discussion of previous homework and implementation issues • MARQS: Presentation and Discussion • Homework

  9. Class Overview • Long Paper discussion (lead by ?) • Brief Lecture on Long • Discussion of previous homework and implementation issues • MARQS: Presentation and Discussion • Homework

  10. Homework • Read Paulson paper. • Invent and better recognition features • Write a paper on the results.

  11. Paper Criteria • CONTENT: • Clarity • Ideas • FORMAT • Abstract • Previous work • Implementation/Methodology • Results • Discussion • Future Work • Conclusion • Bibliography

  12. Paper Criteria: Content • Clarity • There should be no spelling mistakes • There should be no grammar mistakes • Writing should be clear and cogent • Writing should be as brief as possible, i.e., not rambling • Uses images when necessary to clarify ideas • Ideas • Ideas are original • Ideas are interesting

  13. Paper Criteria: Format/Abstract • A one paragraph summary of your paper • One sentence motivation • One sentence what you did • One sentence results • Do not make this a story • People should be able to *only* read your abstract and know exactly what you did

  14. Paper Criteria: Format/Introduction • Introduction/Motivation • Introduce the area • Describe the problem you are trying to solve • Why is this problem important • Provide any background information necessary to understand the problem • Any intelligent person should be able to understand, and be motivated by, your problem

  15. Paper Criteria: Format/Previous Work • List at least 2-3 of the most related work in the field (at a minimum you should have Rubine/2 Long papers/Paulson) • Describe how your work differs from theirs (i.e. why their work does not solve the problem you are trying to solve)

  16. Paper Criteria:Format / Implementation-Methodology • Implementation/Methodology • What did you do? • How did you do it? • How can other people reproduce what you did?

  17. Paper Criteria: Format/Results • Results • What was the outcome of you work? • What statistical test did you use to determine these results (i.e., a t-test / recognition accuracy) • Graphs and tables • Make sure there is some way to measure what you have done

  18. Paper Criteria: Format/Discussion • Analysis of the results • What worked • What didn’t work • Why do you think things worked • Why do you think things didn’t work

  19. Paper Criteria: Format/Future Work • If you had more time to work on this, what would you do next give the results of your paper? Why? • What future ideas naturally extend from this work?

  20. Paper Criteria: Format/Conclusion • Summarize what you told them • What were the key findings • Similar to abstract, but you can assume people have read the paper • What did you want people to get out of the paper? • What should they walk away remembering?

  21. Paper Criteria: Format/Bibliography • References are properly cited • Refer to papers read for proper format.

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