Published in Zeitschrift für wirtschaftlichen Fabrikbetrieb
In modern manufacturing systems, quality monitoring is crucial for efficient and cost-effective production. Conventional systems rely on thresholds and process windows, but machine learning (ML) techniques promise greater accuracy and efficiency. However, pre-processing the data is still timeconsuming. This paper presents an approach to visually ve...
The multimodal nature of clinical assessment and decision-making, and the high rate of healthcare data generation, motivate the need to develop approaches specifically adapted to the analysis of these complex and potentially high-dimensional multimodal datasets. This poses both technical and conceptual problems: how can such heterogeneous data be a...
In today’s digital society, where critical infrastructure is dependent on the integrity and security of network systems, cyber threats pose significant risks to our society. The complexity and volume of data traffic render networks more susceptible to these threats, emphasizing the urgent need for better protective measures. This work investigates ...
Laser powder bed fusion is at the forefront of manufacturing metallic objects, particularly those with complex geometries or those produced in limited quantities. However, this 3D printing method is susceptible to several printing defects due to the complexities of using a high-power laser with ultra-fast actuation. Accurate online print defect det...
The aim of this thesis is to derive an unsupervised method for detecting anomalies in time series. Autoencoder-based approaches are widely used for the task of detecting anomalies where a model learns to reconstruct the pattern of the given data. The main idea is that the model will be good at reconstructing data that does not contain anomalous beh...
Published in Frontiers in Sustainable Cities
In this paper, an innovative approach to detecting anomalous occurrences in video data without supervision is introduced, leveraging contextual data derived from visual characteristics and effectively addressing the semantic discrepancy that exists between visual information and the interpretation of atypical incidents. Our work incorporates Unmann...
Published in SEEU Review
Aquaculture plays a significant role in both economic development and food production. Maintaining an ecological environment with good water quality is essential to ensure the production efficiency and quality of aquaculture. Effective management of water quality can prevent abnormal conditions and contribute significantly to food security. Detecti...
Published in IEEE transactions on pattern analysis and machine intelligence
In this paper, we propose a new method to perform data augmentation in a reliable way in the High Dimensional Low Sample Size (HDLSS) setting using a geometry-based variational autoencoder (VAE). Our approach combines the proposal of 1) a new VAE model, the latent space of which is modeled as a Riemannian manifold and which combines both Riemannian...
Airspace design is subject to a multitude of constraints, which are mainly driven by the concern to keep the risk of mid-air collision below a target level of safety. For that purpose, Monte Carlo simulation methods can be applied to estimate aircraft conflict probability but require the accurate generation of artificial trajectories. Generative mo...
Síťová bezpečnost je v dnešním propojeném světě stále důležitějším problémem, protože počet a složitost hrozeb neustále roste. Federativní učení (FL) je metoda strojového učení, která umožňuje distribuovaně trénovat model s využitím dat klientů a zároveň chránit jejich soukromí. V této práci představujeme FL řešení pro síťovou bezpečnost, konkrétně...
