The Faculty of Mathematics and Natural Sciences: Search
Now showing items 321-330 of 353
Deconstructing and Approaching Heterogeneities in the Biomedical Field via Computational Modeling
(2022-12-06)
Natural variation between human characteristics as well as differences across collected datasets in disparate medical or research centers on various levels (e.g., semantical and technical) lead to high heterogeneity in ...
Quantitative and intuitive liver tumor treatment with multi-constrained planning and holographic augmented reality
(2022-12-15)
In recent years, thermal ablation has become a widely accepted minimal invasive treatment for liver tumor patients. However, surgical planning and performing are still challenging tasks in two aspects: on one hand, surgical ...
Scalable 3D Reconstruction for Immersive Virtual Reality Applications
(2022-12-19)
The recent advances in Augmented Reality (AR) and Virtual Reality (VR) technology and their growing popularity in the past years has significantly influenced emerging trends towards more intuitive and user-centric applications ......
Robust and Interpretable Visual Perception Using Deep Neural Networks
(2023-01-11)
Autonomous vehicles promise to revolutionize the transportation of people and goods by increasing road safety, reducing resource consumption, and improving quality of life. To achieve an unrestricted and large-scale ......
Time Filter Assisted Deep Learning to Predict Air Pollution
(2023-07-13)
Exposure to ground-level ozone harms human health as well as the entire ecosystem, so accurate prediction of ozone exposure is of particular importance. Machine learning (ML), and deep learning (DL) in particular, has ...
Scalable Distributed Machine Learning for Knowledge Graphs
(2023-07-17)
Due to the increasing progress of digitization, immense amounts of data are accumulating, which can be summarized under the term Big Data and form an exciting basis for data analyses. Since the data are heterogeneous and ...
Physically Based Modeling of Micro-Appearance
(2023-07-11)
This dissertation addresses the challenges of creating photorealistic images by focusing on generating and rendering microscale details and irregularities, because a lack of such imperfections is usually the key aspect of ...
Utilization of Reconstructive Representation Learning for Robust Classification
(2023-07-20)
Deep neural networks (DNNs) are generally trained via empirical risk minimization (ERM) on classification tasks. While this has lead to impressive results in scientific benchmarks, as well as, industrial applications, it ...
Automatic Evaluation of Dialogue-Systems Using Neural-Network Methods
(2023-06-05)
We usually interact with computers by means of specialized tools that are not as common as the language humans use. This has motivated researchers for already several decades to develop algorithms that enable interfacing ...
Advancing Knowledge-Enhanced Conversational Systems Leveraging Language Models
(2023-09-18)
Large language models empowering recent conversational systems such as Alexa and Siri require external knowledge to generate informative and accurate dialogues. The knowledge may be provided in structured or unstructured ...