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Agri-environmental schemes are important to promote biodiversity-friendly farming practices. This thesis aims to propose a result-based scheme that uses machine learning to predict species diversity. - Agricultural, Veterinary and Environmental Sciences
- Master Thesis
| Translation averaging is the problem of estimating the global 3D translation of a set of cameras given their orientations and a set of relative translations estimated from image pairs. Translation averaging is a cornerstone in global Structure-from-Motion algorithms. This project is about designing a deep network that iteratively removes incorrect relative translations to estimate the global ones.
- Computer Vision
- Master Thesis, Semester Project
| The goal of this project is to develop an end-to-end differentiable global structure-from-motion algorithm. - Computer Vision
- Master Thesis, Semester Project
| The project aims to compare and evaluate different sensing technologies for contextual intelligence that can detect and classify the presence and movement of people at workplace- or room-level. The current implementation, using infrared sensors, shall be compared to novel ultrasound time-of-flight sensors that are still not commercially available. The project is interested in the achieved tradeoff between accuracy, power consumption, and system limitations. - Digital Systems, Electrical and Electronic Engineering, Environmental Technologies
- Bachelor Thesis, Energy Harvesting (PBL), Firmware (PBL), Machine Learning (PBL), Master Thesis, Microcontroller (PBL), PCB Design (PBL), Semester Project
| The goal is the develop an algorithm that builds a pose graph from an unordered set of images as fast as possible. This is achieved by, first, building a minimal spanning tree from the images exploiting predicted similarity scores. Then the spanning tree is populated with additional edges until the pose uncertainty falls below a threshold in each vertex. This procedure is very important for Structure-from-Motion algorithms where the first step is generated such pose graphs. - Computer Vision
- Master Thesis, Semester Project
| The thesis aims to develop a new bio-inspired robot with a thruster-based adhesion to climb uneven surfaces. - Intelligent Robotics, Robotics and Mechatronics
- Master Thesis
| Minimal solvers are of extreme importance to robust geometric model estimation (e.g., relative camera pose). Automatic generators take a set of input constraints (usually polynomial) and automatically generate a solver that returns the sought model parameters given a set of input data points. None of the recent automatic generators account for the problem of creating differentiable minimal solvers - a problem that gets more and more attention with the success of deep learning-based methods. - Computer Vision
- Master Thesis, Semester Project
| Wearable haptic interfaces are promising for applications in robotics, athletics, rehabilitation, biofeedback-based medical devices and much more. This project will focus on the development of a low-profile wearable interface with on-board processing and actuation to help accelerate motor learning of complex tasks.
Skills: Mechanical engineering, embedded electronics, signal processing, programming, wearables fabrication, interest in dance or rehabilitation applications
- Biomechanical Engineering, Biosensor Technologies, Electrical Engineering, Engineering/Technology Instrumentation, Rehabilitation Engineering
- Collaboration, Internship, Lab Practice, Master Thesis, Semester Project, Student Assistant / HiWi
| The goal of this semester project is to simulate a trap geometry that presents a non quadratic potential. - Electrical and Electronic Engineering, Optical Physics
- Semester Project
| Background
Precision medicine based on cell-based assays has gradually gained popularity and is now essential for the treatment of patients suffering
from diseases with complex treatment regimens, such as rheumatoid arthritis.
Classifying patients according to their synovial fibroblast (SF) functional signature could lead to targeted therapies with a much higher
success rate than currently available disease-modifying drugs. To achieve this goal, we have successfully developed a series of assays that
enable functional screening of synovial fibroblasts and form the basis of a drug discovery approach for more effective personalized
treatment.
Aim
The aim of this work is to develop a model for automatically predicting the cellular stage from single-cell microscopy images, as such a
model would facilitate the personalization of treatments for patients suffering from rheumatic diseases. Therefore, the functional stage of
synovial fibroblasts (SF) - the cells of interest - should be classified into biologically meaningful classes based on physiological processes
such as mitochondrial activity, oxidative stress or apoptosis. Since some cells cannot be clearly assigned to a specific class, it may be
interesting to use not only supervised but also semi- or unsupervised approaches. All in all, the final goal is an easy-to-use pipeline for
single cell segmentation and classification that provides biologically meaningful outputs and visualizations. - Artificial Intelligence and Signal and Image Processing
- Master Thesis
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