Index

Deep learning for Glioma Survival Prediction

Estimation of 3D Implant Pose and Position from 2D X-Ray Images using Transformer Networks

Deep Learning for Bias Field Correction in MRI Scans

Spoken Language Identification for Hearing Aids

Development of a Gamification Platform for Wildlife Identification and Understanding

MASTER’S PROJECT (10 ECTS)

Multiple people required!

 

Welcome to “FinLearn” – an innovative gamification platform aimed at unraveling the mysteries of killer whales through photo identification, engaging users of all ages in an immersive learning experience. As developers, you have the opportunity to shape this platform into a captivating educational tool that inspires curiosity and fosters understanding about these majestic creatures.

FinLearn leverages state-of-the-art deep learning algorithms to analyze vast collections of killer whale images, allowing users to explore their distinctive markings, behaviors, and ecological roles. Through interactive modules and challenges, users embark on a captivating journey, learning about orca social dynamics, migration patterns, and the importance of conservation efforts.

Your role as developers is crucial in crafting engaging quests, challenges, and interactive elements that bring the world of killer whales to life. Whether it’s annotating photo identifications, analyzing behavioral cues, or exploring virtual marine environments, your creativity and expertise will shape the user experience and inspire a sense of wonder and discovery.

Furthermore, FinLearn fosters collaboration and community engagement, providing users with opportunities to share insights, discuss findings, and collaborate on research projects. By integrating discussion forums, collaborative initiatives, and leaderboards, you can create a vibrant learning community that transcends age barriers and geographical boundaries.

Together, let’s embark on this exciting journey of exploration and conservation. With FinLearn, you have the power to ignite a passion for marine science and conservation in users of all ages, inspiring a new generation of stewards committed to protecting the future of killer whales and their ocean habitats.

 

 

Project Requirements:

Required: Programming experience.

Nice to have: Experience in .NET, Angular, database design, web design, and familiarity with microservice architectures (Kubernetes, Docker)

Definition und Implementierung einer prototypischen Smart Home Schnittstelle für ein cloudbasiertes Energiemanagementsystem

Deep Learning-Based Breast Density Categorization in Asian Women

thesisdescription

Improvements in SSL image-text learnings on CXR images

Deep Learning based Collimator Detection

Transformers vs. Convolutional Networks for 3D segmentation in industrial CT data

The current state of the art for segmentation in industrial CT are oftentimes CNNs.
Transformer based models are sparsely used.
Therefore, this project wants to compare the semantic segmentation performance of transformers (that include global context into segmentation), pure convolutional neural networks (that use local context) and combined methods (like this one: https://doi.org/10.1186/s12911-023-02129-z) on an industrial CT dataset of shoes like in this study: https://doi.org/10.58286/27736 .

Only available as Bachelors thesis / Research Project