Auflistung nach Schlagwort "machine learning"
Anzeige der Dokumente 1-19 von 19
-
Agri-food policies and Sustainable Development Goals: Quantitative food system analyses
Latka, Catharina (2022-08-23)The agricultural and food system is key to reaching several of the Sustainable Development Goals (SDGs), foremost those on food security (SDG2), reducing waste (SDG12), combatting climate change (SDG13), and reducing ... -
Ai-based, behavior dependent approaches for connectomic reconstruction of neuronal circuits
Schweihoff, Jens Florian (2022-03-24)Characterizing the functional architecture of neuronal circuits that underly complex behavior requires identifying active neuronal ensembles during behavioral expressions of interest. The recent development of light-induced, ... -
Analysis of Multitarget Activities and Assay Interference Characteristics of Pharmaceutically Relevant Compounds
Jasial, Swarit (2019-05-29)The availability of large amounts of data in public repositories provide a useful source of knowledge in the field of drug discovery. Given the increasing sizes of compound databases and volumes of activity data, computational ... -
Challenges related to statistical methods and sensor systems for the daily prediction of health disorders in individual dairy cows
Post, Christian (2023-02-02)The use of digital support systems has become a standard in dairy farming, and significant effort has been made to detect individual animals that are in need for a treatment by using sensor data. However, developing systems ... -
Chemoinformatics-Driven Approaches for Kinase Drug Discovery
Miljković, Filip (2020-01-07)Given their importance for the majority of cell physiology processes, protein kinases are among the most extensively studied protein targets in drug discovery. Inappropriate regulation of their basal levels results in ... -
Deep Generative Modelling in Systems Medicine: From Transcriptomics Data to Drug Development
Oestreich, Marie (2024-02-02)(noch nicht zugänglich / not yet accessible) -
Deep Phenotyping of disease resistance based on hyperspectral imaging and data mining methods in high throughput
Brugger, Anna (2022-12-12)Hyperspectral imaging for plant phenotyping has become an established research method using the visible to short wave infrared range (400-2500 nm). This allows for the differentiation, identification, and quantification ... -
Dissecting patient heterogeneity via statistical modeling based on multi-modal omics data
Ahmad, Ashar (2019-06-27)One of the key goals of modern medicine is to treat patients individually, recognizing the heterogeneity that exists within them and thus hoping to provide them with more effective personalized therapies. '-Omics' patient ... -
From Limited Data to Meaningful Insights: Two studies on chronic stress prediction using machine learning
Bozorgmehr, Arezoo (2024-02-01)Background: Chronic stress is widespread and adversely affects mental and physical health. The two studies in this dissertation used machine learning to predict chronic stress and identify its risk as well ... -
Hyperspectral Imaging for Non-Invasive Characterization of Barley Resistances to Powdery Mildew
Kuśka, Matheus Thomas (2017-11-10)Determination and characterization of resistance reactions of crop plants against fungal pathogens are essential to select resistant genotypes. In breeding practice phenotyping of genotypes is realized by time consuming ... -
Investigation of BCRP-inhibitors using QSAR and machine learning methods
Marighetti, Federico (2019-08-05)BCRP is the second member of the subfamily G of the ABC transporters. BCRP is involved in several physiological functions, including protection of the human body from xenobiotics. The overexpression of this membrane protein ... -
Mapping and Interpolation of Tropospheric Ozone Data with Machine Learning Methods
Betancourt, Clara (2023-12-14)Tropospheric ozone is a toxic trace gas in the atmosphere. It threatens human health, damages crops and vegetation, and it is a short-lived climate forcer. Ozone is a secondary air pollutant that undergoes multiple physical ... -
A memory-based quantum network node with a trapped ion in an optical fibre cavity
Kobel, Pascal (2022-06-17)Exploiting quantum effects in the communication between different systems promise great capabilities as distributed quantum computing or provably secure communication. In this thesis we present the realisation of a ... -
Novel Search Techniques to Detect Pulsar Black Hole Binaries in Radio Observations
Balakrishnan, Vishnu (2022-02-21)Pulsars are rapidly rotating highly magnetised neutron stars that emit beams of electromagnetic radiation from their magnetic poles. These compact objects are unique as they are one of the densest forms of matter known in ... -
Predicting Rules for Cancer Subtype Classification using Grammar-Based Genetic Programming on various Genomic Data Types
Deng, Mario (2018-03-12)With the advent of high-throughput methods more genomic data then ever has been generated during the past decade. As these technologies remain cost intensive and not worthwhile for every research group, databases, such as ... -
Shape and Topology Constrained Image Segmentation with Stochastic Models
Zöller, Thomas (2005)The central theme of this thesis has been to develop robust algorithms for the task of image segmentation.
All segmentation techniques that have been proposed in this thesis are based on the sound modeling of the ... -
Similarities and Representations of Graph Structures
Tsitsulin, Anton (2021-06-01)Graphs are a natural representation for diverse systems ranging from social networks to the Web and brain structure. Even when data is not interconnected explicitly, it is often convenient to convert it into a graph for ... -
Spectral Properties of the Kernel Matrix and their Relation to Kernel Methods in Machine Learning
Braun, Mikio Ludwig (2005)Machine learning is an area of research concerned with the construction of algorithms which are able to learn from examples. Among such algorithms, so-called kernel methods form an important family of algorithms which have ... -
Using Advanced Machine Learning Techniques to Study Poorly Modeled Processes in pp Collisions with the ATLAS Detector
Diaz Capriles, Federico Guillermo (2023-07-12)In high energy particle physics, measurements are made to improve and test our models. Some processes are difficult or impossible to model with current capabilities. For some, this means that one would estimate such processes ...