most citedTowards practicable Machine Learning development using AI Engineering Blueprints

1 citations · 1 across the 5 of their papers we have counts for

collaborators

6 papers

eess.SP2026

Comparison of Dimension Reduction Methods for EEG Seizure Detection Using Autonomous AI-Driven Optimization

Annika Stiehl, Vishal Kagade, Nicolas Weeger +3

Automated epileptic seizure detection from multichannel electroencephalography (EEG) benefits from dimension reduction to obtain compact, discriminative representations. We compare…

eess.SP2026

Low-Density EEG for Seizure Detection: Evaluating CNN-RNN Architectures on a Behind-the-Ear Montage Setup

Annika Stiehl, Patrick Wingert, Nicolas Weeger +3

Epilepsy affects over 50 million individuals globally, underscoring the need for automated seizure detection systems that can alleviate clinicians workload and enhance the accuracy…

cs.SE2026

AI Engineering Blueprint for On-Premises Retrieval-Augmented Generation Systems

Nicolas Weeger, Jakob Winkler, Annika Stiehl +3

Retrieval-augmented generation (RAG) systems are gaining traction in enterprise settings, yet stringent data protection regulations prevent many organizations from using cloud-base…

eess.SP2025

Towards Automated EEG-Based Epilepsy Detection Using Deep Convolutional Autoencoders

Annika Stiehl, Nicolas Weeger, Christian Uhl +3

Epilepsy is one of the most common neurological disorders. This disease requires reliable and efficient seizure detection methods. Electroencephalography (EEG) is the gold standard…

cs.SE2025★ 1 cited

Towards practicable Machine Learning development using AI Engineering Blueprints

Nicolas Weeger, Annika Stiehl, Jóakim vom Kistowski +2

The implementation of artificial intelligence (AI) in business applications holds considerable promise for significant improvements. The development of AI systems is becoming incre…

eess.SP2025

Dimension reduction methods, persistent homology and machine learning for EEG signal analysis of Interictal Epileptic Discharges

Annika Stiehl, Stefan Geißelsöder, Nicole Ille +3

Recognizing specific events in medical data requires trained personnel. To aid the classification, machine learning algorithms can be applied. In this context, medical records are…