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Theses and Projects: Difference between revisions
→* New! Edge-Cloud Orchestration for LiDAR-based Traffic Analysis
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* (M) Master thesis | * (M) Master thesis | ||
* (P) Student project | * (P) Student project | ||
=== * '''New!''' Efficient Live Volumetric Video Streaming System=== | |||
The exponential growth of digital data and multimedia content necessitates robust and efficient systems to handle the streaming of high-resolution, three-dimensional volumetric videos. These videos offer a more immersive and realistic experience, making them increasingly used in various sectors such as virtual reality, augmented reality, and entertainment. The challenge here lies in creating a system that can handle the high-bandwidth and computation-intensive demands of live volumetric video streaming while ensuring the delivery of a seamless and high-quality user experience. This project conceptualizes the development and optimization of efficient algorithms and systems to handle volumetric video streams, mitigating bandwidth cost and latency issues. We expect you to have a background in video streaming technologies, computer vision, and programming skills. | |||
Please contact Yanlong Huang[yanlong.huang@cs.uni-goettingen.de] | |||
=== * '''New!''' Edge-Cloud Orchestration for LiDAR-based Traffic Analysis=== | |||
The imminent era of smart cities and autonomous vehicles paves the way for the deployment and operation of advanced monitoring and processing systems. Among these, LiDAR technology stands out for its ability to provide high-resolution, three-dimensional traffic data, becoming an essential component for efficient traffic analysis and management. However, the computation-intensive and latency-sensitive nature of LiDAR data processing poses significant challenges and dictates the need for efficient orchestration between edge and cloud computing resources. Edge-Cloud Orchestration offers an innovative solution to this problem by bridging the gap between these two technologies, enabling the low-latency processing of complex LiDAR data. It would be good if you have a background in point cloud processing/cloud computing, K8s, and programming skills. | |||
Please contact Yanlong Huang[yanlong.huang@cs.uni-goettingen.de] | |||
=== * '''New!''' Blockchain-based Spectrum and Computation Resources Sharing in Mobile Networks=== | |||
The sixth-generation (6G) system is widely envisioned as a global network consisting of pervasive devices that interact with each other. Besides exchanging information, these peer entities also share heterogeneous and distributed network resources. Blockchain is a promising technology to secure resource sharing in a peer-to-peer way. We need students for this topic. We expect you have a background in computer network and programming skills in Python. | |||
Please contact Jin Xie [jin.xie@stud.uni-goettingen.de] | |||
=== * '''New!''' Using LLM for Sentiment Knowledge Graph Construction (B/M/P)=== | |||
Constructing a sentiment knowledge graph using Large Language Models (LLMs) like ChatGPT involves leveraging the model's capabilities to understand and analyze textual data, extract entities and relationships, perform sentiment analysis, and organize the information into a graph structure. We need students for this topic. We expect you have a background in knowledge graph and programming skills in Python. | |||
Please contact Wenfang Wu [wenfang.wu@cs.uni-goettingen.de] | |||
=== * '''New!''' Using LLM for Knowledge Graph Completion (B/M/P)=== | |||
Large language models (LLMs), such as ChatGPT and GPT-4 (OpenAI, 2023), have extensive internal knowledge repositories from their vast pretraining corpora, which can be used as an extra knowledge base to alleviate information scarcity for the long-tail entities in Knowledge Graphs. However, there is no effective workflow design for LLM on KGC tasks. How to leverage the LLM to perform reasoning on the KG Completion (KGC) task is a noteworthy and significant topic. We need students for this topic. We expect you to have a background in knowledge graph and LLMs, you'd better have a programming skill in Python. | |||
Please contact Tong Shen [shen.tong@cs.uni-goettingen.de] | |||
=== * '''New!''' Tree Growth Detection using Satellite Images and Computer Vision Methods (B/M/P) === | === * '''New!''' Tree Growth Detection using Satellite Images and Computer Vision Methods (B/M/P) === | ||
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Please contact Fabian Wölk [fabian.woelk@cs.uni-goettingen.de] | Please contact Fabian Wölk [fabian.woelk@cs.uni-goettingen.de] | ||
=== * | === * 3D natural hazard simulator === | ||
The aim of the project is to simulate representative natural hazards for hazard response, such as flooding and forest fire. A natural hazard response simulator will be implemented for both visualization and performance validation. For example, we can visualize the flooding of 2021 in Germany, and then validate the performance of drone deployment in hazard sensing and emergency communication. Here, we introduce some related works in virtual 3D scene which may help you to understand this project, e.g., Agents Toolkit (ML-Agents) [1], DisasterSim [2] and Airsim [3]. | The aim of the project is to simulate representative natural hazards for hazard response, such as flooding and forest fire. A natural hazard response simulator will be implemented for both visualization and performance validation. For example, we can visualize the flooding of 2021 in Germany, and then validate the performance of drone deployment in hazard sensing and emergency communication. Here, we introduce some related works in virtual 3D scene which may help you to understand this project, e.g., Agents Toolkit (ML-Agents) [1], DisasterSim [2] and Airsim [3]. | ||
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Please contact Prof. Xiaoming Fu [fu@cs.uni-goettingen.de](B/M/P) | Please contact Prof. Xiaoming Fu [fu@cs.uni-goettingen.de](B/M/P) | ||
=== * '''Occupied''' OCR (Optical Character Recognition) and Annotation Transfer === | === * '''[Occupied]''' OCR (Optical Character Recognition) and Annotation Transfer === | ||
The aim of the project is to develop a tool/software that can convert a printed paper with annotations and text into electronic versions with text highlighting and annotations. The successful candidate will be responsible for developing this tool/software that can perform the following tasks: | The aim of the project is to develop a tool/software that can convert a printed paper with annotations and text into electronic versions with text highlighting and annotations. The successful candidate will be responsible for developing this tool/software that can perform the following tasks: | ||
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Please contact Dr. Tingting Yuan [tingting.yuan@cs.uni-goettingen.de]] (B/M/P) | Please contact Dr. Tingting Yuan [tingting.yuan@cs.uni-goettingen.de]] (B/M/P) | ||
=== | === * Privacy-preserved Video Analytics=== | ||
This project/thesis topic focuses on the protection of privacy in | This project/thesis topic focuses on the protection of privacy in video analytics. | ||
The project involves three key tasks: | The project involves three key tasks: | ||
1) Implementation of a system utilizing YOLO and CycleGANs/DataGen for video analysis and processing. | 1) Implementation of a system utilizing YOLO and CycleGANs/DataGen for video analysis and processing. The code for this is already available for use. | ||
2) Development of a privacy protection mechanism by adjusting the level of blur applied to the video, taking into account a trade-off between inference accuracy (e.g. detection by YOLO) and the level of privacy protection. | 2) Development of a privacy protection mechanism by adjusting the level of blur applied to the video, taking into account a trade-off between inference accuracy (e.g., detection by YOLO) and the level of privacy protection. | ||
3) | 3) Optimize the blur level for Pan-tilt-zoom cameras to ensure that the system effectively captures key visual information while still preserving privacy. | ||
Please contact Dr. Tingting Yuan [tingting.yuan@cs.uni-goettingen.de] (B/M/P) | Please contact Dr. Tingting Yuan [tingting.yuan@cs.uni-goettingen.de] (B/M/P) | ||
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=== Super resolution technique for efficient video delivery === | === [Closed] Super resolution technique for efficient video delivery === | ||
Super-resolution (SR) is one of the fundamental tasks in Computer vision. Video delivery on Internet or in WAN is important for various applications, eg., video analytics and video viewing. This project attempts to explore the potential of SR for video delivery. We expect you have Data Science and Computer Vision background, as well as programming skills like Python. | |||
Please contact Weijun Wang [weijun.wang@informatik.uni-goettingen.de] (B/M/P) | Please contact Weijun Wang [weijun.wang@informatik.uni-goettingen.de] (B/M/P) | ||
=== [closed] Assessing city livability with big data === | === [closed] Assessing city livability with big data === | ||
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Please contact Dr.Tingting Yuan [tingting.yuan@cs.uni-goettingen.de ] and Weijun Wang [weijun.wang@informatik.uni-goettingen.de](B/M/P) | Please contact Dr.Tingting Yuan [tingting.yuan@cs.uni-goettingen.de ] and Weijun Wang [weijun.wang@informatik.uni-goettingen.de](B/M/P) | ||
== Ongoing Topics == | == Ongoing Topics == | ||
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|{{Hl2}} |'''Description''' | |{{Hl2}} |'''Description''' | ||
|{{Hl2}} |'''Student''' | |{{Hl2}} |'''Student''' | ||
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| OCR (Optical Character Recognition) and Annotation Transfer (Bachelor Project+Thesis) | |||
|[http://www.net.informatik.uni-goettingen.de/?q=people/dr-tingting-yuan Tingting Yuan] | |||
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| Assigned to Jiaying | |||
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| AI for Games (Bachelor Project+Thesis) | |||
|[http://www.net.informatik.uni-goettingen.de/?q=people/dr-tingting-yuan Tingting Yuan] | |||
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| Completed by Jason | |||
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| Neural video analytics(Master Thesis) | |||
|[http://www.net.informatik.uni-goettingen.de/?q=people/dr-tingting-yuan Tingting Yuan] | |||
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| Completed by Mai | |||
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| Submodel Federated learning (Bachelor Project + Thesis) | |||
|[http://www.net.informatik.uni-goettingen.de/?q=people/dr-tingting-yuan Tingting Yuan] | |||
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| Completed by Zilin | |||
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|Bio-Data analysis (Student project) | |Bio-Data analysis (Student project) | ||