Seminar on Internet Technologies (Winter 2020 2021): Difference between revisions

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| [Xiaoming, xfu@gwdg.de]
| [Xiaoming, xfu@gwdg.de]
|-
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| Objects detection in Autonomous driving (assigned)
| Objects detection in Autonomous driving (example)
| Analysis the autonomous driving dataset by some machine learning methods.
| Analysis the autonomous driving dataset by some machine learning methods.
| Basic programming knowledge, Basic machine learning knowledge
| Basic programming knowledge, Basic machine learning knowledge

Revision as of 14:44, 22 September 2020

Details

Workload/ECTS Credits: 5 ECTS (BSc/MSc AI); 5 (ITIS)
Lecturer: Prof. Xiaoming Fu
Teaching assistant: TingTing Yuan,Shichang Ding and Sripriya Srikant Adhatarao
Time: Nov 4th. Please read this introduction slide (https://drive.google.com/open?id=1jNZ-k8WSu4tP6bMHvY73FBoUXdrXNLql). If there is any question, please contact teaching assistants.
Place: Through Zoom, waiting link
UniVZ [1]


Imbox content.png Note:

Course description

This course covers selected topics on the up-to-date Internet technologies and research. Each student takes a topic, does a presentation and writes a report on it. Besides the introduction meeting, there are no regular meetings, lectures or classes for this course. The purpose of this course is to familiarize the students with new technologies, enable independent study of a specific topic, and train presentation and writing skills.

The informational meeting at the beginning of the course will cover some guidelines on scientific presenting and writing.

Due to topic advisors' workload limitation, we could only provide limited topics, and the topic assignment will be on the basis of first come first serve principle. Please contact the topic advisor directly for the topic availability.

Note: Participants in the seminar only need to register the exam before the end of the course.

Passing requirements

  • There will be 2 milestones before the presentations where the students should pass before they register for the course.
    • Intro milestone where the adviser make sure that the student starts to work on the topic and follows an accepted methodology.
    • Midterm milestone. (ex. programming tasks done etc... )
  • Actively and frequently participate in the project communication with your topic advisor
    • This accounts for 20% of your grade.
  • Present the selected topic (20 min. presentation + 10 min. Q&A).
    • This accounts for 40% of your grade.
  • Write a report on the selected topic (12-15 pages) (LaTeX Template:[2]).
    • This accounts for 40% of your grade.
  • Please check the #Schedule and adhere to it.

Schedule

Will be updated!!!

  • Decemeber 30th, 2020  : Deadline for registration
  • Jan. 6 (13:00-16:00) and Jan. 7 2021 (13:00-16:00) : Final Presentations at IFI Building Room 1.101
  • May. 5, 2021, 23:59: Deadline for submission of report (should be sent to the topic adviser!) Follow this deadline instead of another one in Flex now

Topics

Topic Description Prerequisites Topic Advisor Initial Readings
Visible Light Communications: Principles, Standardization and Applications (assigned) [Xiaoming, xfu@gwdg.de]
Objects detection in Autonomous driving (example) Analysis the autonomous driving dataset by some machine learning methods. Basic programming knowledge, Basic machine learning knowledge [Yali Yuan, yali.yuan@cs.uni-goettingen.de] [3]

Workflow

1. Select a topic

A student picks a topic to work on. You can pick up a topic and start working at any time. However, make sure to notify the advisor of the topic before starting to work.

2. Get your work advised

For each topic, a topic advisor is available. He is your contact person for questions and problems regarding the topic. He supports you as much as you want, so please do not hesitate to approach him for any advice or with any questions you might have. It is recommended (and not mandatory) that you schedule a face-to-face meeting with him right after you select your topic.

3. Approach your topic

  • By choosing a topic, you choose the direction of elaboration.
  • You may work in different styles, for example:
    • Survey: Basic introduction, an overview of the field; general problems, methods, approaches.
    • Specific problem: Detailed introduction, details about the problem and the solution.
  • You should include your own thoughts on your topic.

4. Prepare your presentation

  • Present your topic to the audience (in English).
  • 20 minutes of presentation followed by 10 minutes discussion.

You present your topic to an audience of students and other interested people (usually the NET group members). Your presentation should give the audience a general idea of the topic and highlight interesting problems and solutions. You have 20 minutes to present your topic followed by 10 minutes of discussion. You must keep it within the time limit. Please send your slides to your topic advisor for any possible feedback before your presentation.

Hints for preparing the presentation: 20 minutes are too short to present a topic fully. It is alright to focus just on one certain important aspect. Limit the introduction of basics. Make sure to finish in time.

Suggestions for preparing the slides: No more than 20 pages/slides. Get your audiences to quickly understand the general idea. Figures, tables and animations are better than sentences. Summary of the topic: thinking in your own words.

5. Write your report

  • Present the problem with its background.
  • Detail the approaches, techniques, methods to handle the problem.
  • Evaluate and assess those approaches (e.g., pros and cons).
  • Give a short outlook on potential future developments.

The report must be written in English according to common guidelines for scientific papers, between 12 and 15 pages of content (excluding the table of content, bibliography, etc.).

6. Course schedule

There are no regular meetings, lectures or classes for this course. The work is expected to be done by yourself with the assistance of your topic advisor. Please follow the #Schedule to take appropriate actions.