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Seminar on Internet Technologies (Summer 2021): Difference between revisions

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Created page with "== Details == {{CourseDetails |credits=5 ECTS (BSc/MSc AI); 5 (ITIS) |lecturer=[http://user.informatik.uni-goettingen.de/~fu Prof. Xiaoming Fu] |ta =Tingting Yuan [tingting.yua..."
 
 
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|credits=5 ECTS (BSc/MSc AI); 5 (ITIS)
|credits=5 ECTS (BSc/MSc AI); 5 (ITIS)
|lecturer=[http://user.informatik.uni-goettingen.de/~fu Prof. Xiaoming Fu]
|lecturer=[http://user.informatik.uni-goettingen.de/~fu Prof. Xiaoming Fu]
|ta =Tingting Yuan [tingting.yuan@cs.uni-goettingen.de], [http://www.net.informatik.uni-goettingen.de/people/shichang_ding Shichang Ding] and  [http://www.net.informatik.uni-goettingen.de/people/sripriya%20srikant_adhatarao, Sripriya Srikant Adhatarao]  
|ta =[http://www.net.informatik.uni-goettingen.de/?q=people/jiaquan-zhang MSc. Jiaquan Zhang];
|time=Nov 4th. Register on ecampus before Nov 8th.'''Please read this introduction slide [https://docs.google.com/presentation/d/13hmKYBmB4tbTFNeK1GvBAs1qZntMYo75o8ycb1NgYXI/edit?usp=sharing]. If there is any question, please contact teaching assistants.'''
|time=April 12th. '''Please read this introduction slide [https://docs.google.com/presentation/d/13hmKYBmB4tbTFNeK1GvBAs1qZntMYo75o8ycb1NgYXI/edit?usp=sharing]. If there is any question, please contact teaching assistants.'''
|place=Through Zoom, waiting link
|place=Through Zoom, waiting link
|univz=[https://univz.uni-goettingen.de/qisserver//rds?state=verpublish&status=init&vmfile=no&publishid=262017&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung]
|univz=[https://univz.uni-goettingen.de/qisserver/rds?state=verpublish&status=init&vmfile=no&publishid=266853&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung]
}}
}}


==Announcement==
==Announcement==
Our final presentation will be held on 24th Jun. 2021 (14:00-18:00) throught Meetings in StudIP.
Due to the recent situations in the context of Covid-19, new information will be updated here in time, please check this webpage periodically to get the newest information.
Due to the recent situations in the context of Covid-19, new information will be updated here in time, please check this webpage periodically to get the newest information.


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==Schedule==
==Schedule==
* '''7th Nov. 2020 ''': Deadline for registration the course
* '''17th Apr. 2021 ''': Deadline for registration the course
* '''20th Jan. 2021 ''': Deadline for registration to attend the final presentation
* '''23h Jun. 2021 ''': Deadline for registration to attend the final presentation
* '''28th Jan. 2021 (14:00-18:00)''' : Final Presentations online (waiting for the link)
* '''24th Jun. 2021 (14:00-18:00)''' : Final Presentations online (Throught Meetings in StudIP)
* '''28th March 2021 (23:59) ''': Deadline for submission of the report (should be sent to the topic adviser!).
* '''24th Aug. 2021 (23:59) ''': Deadline for submission of the report (should be sent to the topic adviser!).


== Topics ==
== Topics ==
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|{{Hl2}} |'''Available'''
|{{Hl2}} |'''Available'''
|-
|-
| Physics-informed neural networks: Principles, Case studies, and Prospects
|Event detection from microblog
| In this project, you will be devoted to solving a specific problem using
| In this topic, you will study how to detect events from microblog, like Twiter.
physics-informed neural networks with a small set of experiment data,
which is different from big data-driven machine learning. The idea of
using neural networks in the research field of Physics is nowadays more
and more significant. The student is expected to be interested in the
the interdisciplinary subject of physics and computer science.
| Basic programming knowledge, Basic machine learning knowledge
| Basic programming knowledge, Basic machine learning knowledge
| [Yunxiao Zhang, yunxiao.zhang@ds.mpg.de]
| [Tingting Yuan, tingting.yuan@cs.uni-goettingen.de]
| [https://www.sciencedirect.com/science/article/pii/S0045782520305879?via%3Dihub]
|[https://dl.acm.org/doi/10.1145/3377939],[https://dl.acm.org/doi/10.1145/3184558.3186338],[https://ieeexplore.ieee.org/document/9094110],[https://dl.acm.org/doi/10.1145/3161193],[https://link.springer.com/chapter/10.1007%2F978-981-13-2922-7_7]
| Yes
|-
|Comparative study of video analytic platforms and algorithms using neural networks: Principles, Standard Algorithms, and Open issues
| In this topic, you will study and analyze the existing video analysis platforms and standard machine learning and deep learning algorithms with small set of experiment data, especially the data from sensor networks. The student is expected to have prior knowledge/experience in data science and programming skills.
| Basic programming knowledge, Basic machine learning knowledge
| [http://www.net.informatik.uni-goettingen.de/?q=people/sripriya-srikant-adhatarao Sripriya Adhatarao]
|
| No
| No
|-
|-
| Graph neural network
| In this topic, you will study graph neural networks (GNNs), which are connectionist models that capture the dependence of graphs via message passing between the nodes of graphs.
| Basic programming knowledge, Basic machine learning knowledge
| [Tingting Yuan, tingt.yuan@hotmail.com]
|[https://arxiv.org/pdf/1812.08434.pdf?source=post_page]
| No
|-
|-
|AI painter
|QoE modelling
| In this topic, you will study how AI has been used for painting.
| In this topic, you will explore how Quality of Experience (QoE) is modelled for multimedia services with machine learning.
| Basic programming knowledge, Basic machine learning knowledge
| Basic programming knowledge, Basic machine learning knowledge
| [Tingting Yuan, tingt.yuan@hotmail.com]
| [Tingting Yuan, tingting.yuan@cs.uni-goettingen.de]
|[https://topten.ai/ai-painting-generators/]
|[https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8922616]
[https://bib.irb.hr/datoteka/1055654.MultimediaQoE.pdf]
[https://www.etsi.org/deliver/etsi_tr/102600_102699/102643/01.00.01_60/tr_102643v010001p.pdf]
[https://arxiv.org/pdf/2007.10878.pdf]
| No
| No
|-
|-
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| In this topic, you will study the entanglement routing problem in a quantum network, which is a novel network built on quantum mechanics.
| In this topic, you will study the entanglement routing problem in a quantum network, which is a novel network built on quantum mechanics.
| Basic programming knowledge, Basic mathematical programming knowledge
| Basic programming knowledge, Basic mathematical programming knowledge
| [Bangbang Ren, bangbang.ren@cs.uni-goettingen.de]
| [Bangbang Ren, renbangbang15@gmail.com]
|[https://dl.acm.org/doi/10.1145/3387514.3405853]
|[https://dl.acm.org/doi/10.1145/3387514.3405853]
| Yes
| Yes
|-
|-
| Video Analytics
| Sensing for flood detection
| Artificial Intelligence has been and is going to be popular for many years. Static object detection, recognition technique has been studied for many years. However, how these techniques work in a dynamic environment (eg. Self-driving ) is not clear. In this topic, we want to reveal which kind of technique performs better in a video surveillance system with limited computing and network resources. Based on this, our goal is to develop a real Wireless Moving Video Surveillance System which including video analysis, wireless data delivery, and data compression and fusion. Fortunately, we already have some preliminary work.  
| You will study methods to monitor water bodies (e.g. rivers) with sensors and how their data can be analyzed to detect upcoming floods and identify affected areas.
| Interested in this topic, willing to follow the advisor's guidance, patience and time for reading multiple papers. Interested in embedded development, we will use Raspberry Pi and NVIDIA Jetson Nano Developer Kit. Have Fun With This Project!
| Basic machine learning knowledge
| [Weijun Wang, weijun.wang@informatik.uni-goettingen.de]
| Fabian Wölk, fabian.woelk@cs.uni-goettingen.de]
| [https://www.microsoft.com/en-us/research/wp-content/uploads/2017/08/Bahl-MobiCom-2015.pdf]
|
| No
|-
| Modelling and simulations of floods
| You will study methods to model and simulate flood flows and how this can be used to identify affected areas of potential floods.
| Basic machine learning knowledge, Basic mathematical knowledge (knowledge in numerical mathematics can be advantageous)
| Fabian Wölk, fabian.woelk@cs.uni-goettingen.de]
|
| Yes
| Yes
|-
|-
| Data augmentation with generative adversarial network (GAN)
| Super-resolution technique for efficient video delivery
| Image classification datasets are often imbalanced, characteristic that negatively affects the accuracy of deep-learning classifiers. In this topic, you will learn to use GAN  as an augmentation tool to restore balance in imbalanced datasets. This is challenging because the few minority-class images may not be enough to train a GAN.  
| Super-resolution (SR) is one of the fundamental tasks in Computer vision. You will learn how to train and use it.  
| Familiar with machine learning and deep learning; image processing with using python;
|Data Science and Computer Vision background, as well as programming skills like Python.
| [Yachao Shao, yachao.shao@cs.uni-goettingen.de]
|Weijun Wang [weijun.wang@informatik.uni-goettingen.de]
| [https://arxiv.org/abs/1803.09655]
|
| Yes
| Yes
|-
|-
| Passenger flow prediction with machine learning
|A survey of smart metering and energy grid: Principles, Standards, and Open issues (Assigned)
| You will study existing methods and algorithms used for the prediction of passenger flow in an urban area to determine the demand for buses, trams or trains.  
| In this topic, you will study and analyze the existing and upcoming energy grid, smart metering and related standards.
| Basic machine learning knowledge
| Basic computer networks knowledge  
| [Fabian Wölk, fabian.woelk@cs.uni-goettingen.de]
| Jiaquan Zhang
|  
|  
| No
|-
| Optimization of public transport schedules
| You will study techniques and algorithms to optimize the schedules for public transport systems.
| Basic machine learning knowledge, Basic mathematical knowledge (knowledge in mathematical optimization problems can be helpful, but is not mandatory)
| [Fabian Wölk, fabian.woelk@cs.uni-goettingen.de]
|
| No
|-
| Automatic Classification of Time Series (ACTS)
| In this project you will apply machine learning techniques to identify differences and similarities in the evolution of real-world phenomena across different regions and countries, like the spread of the SARS-CoV2 virus. The student is expected to have prior knowledge in data science and programming skills.
| Basic programming knowledge, basic machine learning knowledge
| Pablo Gutierrez-Marques p.gutierrezmarques01@stud.uni-goettingen.de
|  [https://doi.org/10.1080/014311600210308]  [https://doi.org/10.1109/ICDE.2017.68]
| No
| No
|-
|-
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* Give a short outlook on potential future developments.
* 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.).
The report must be written in English according to common guidelines for scientific papers, between 12 and 15 pages of content (excluding bibliography, etc.).
Please note that you can not directly copy content from papers or webpages, as this will be considered plagiarism. All quoted images and tables need to indicate their source.
Please note that you can not directly copy content from papers or webpages, as this will be considered plagiarism. All quoted images and tables need to indicate their source.


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