b'Niklas K\xc3\xbchl'

research

∙ 09/03/2023

AB2CD: AI for Building Climate Damage Classification and Detection

We explore the implementation of deep learning techniques for precise bu...

0 Maximilian Nitsche, et al. ∙

research

∙ 07/25/2023

The Impact of Imperfect XAI on Human-AI Decision-Making

Explainability techniques are rapidly being developed to improve human-A...

0 Katelyn Morrison, et al. ∙

research

∙ 05/12/2023

Conceptualizing A Multi-Sided Platform For Cloud Computing Resource Trading

Cost-effective and responsible use of cloud computing resources (CCR) is...

0 Franziska Haller, et al. ∙

research

∙ 05/12/2023

ML-Based Teaching Systems: A Conceptual Framework

As the shortage of skilled workers continues to be a pressing issue, exa...

0 Philipp Spitzer, et al. ∙

research

∙ 04/19/2023

On the Perception of Difficulty: Differences between Humans and AI

With the increased adoption of artificial intelligence (AI) in industry ...

0 Philipp Spitzer, et al. ∙

research

∙ 04/14/2023

Learning to Defer with Limited Expert Predictions

Recent research suggests that combining AI models with a human expert ca...

0 Patrick Hemmer, et al. ∙

research

∙ 03/28/2023

Enabling Inter-organizational Analytics in Business Networks Through Meta Machine Learning

Successful analytics solutions that provide valuable insights often hing...

0 Robin Hirt, et al. ∙

research

∙ 02/23/2023

Parameter-free shape optimization: various shape updates for engineering applications

In the last decade, parameter-free approaches to shape optimization prob...

0 Lars Radtke, et al. ∙

research

∙ 02/17/2023

An Incremental Singular Value Decomposition Approach for Large-Scale Spatially Parallel Distributed but Temporally Serial Data – Applied to Technical Flows

The paper presents a strategy to construct an incremental Singular Value...

0 Niklas Kühl, et al. ∙

research

∙ 02/07/2023

Towards Meaningful Anomaly Detection: The Effect of Counterfactual Explanations on the Investigation of Anomalies in Multivariate Time Series

Detecting rare events is essential in various fields, e.g., in cyber sec...

0 Max Schemmer, et al. ∙

research

∙ 02/04/2023

Appropriate Reliance on AI Advice: Conceptualization and the Effect of Explanations

AI advice is becoming increasingly popular, e.g., in investment and medi...

0 Max Schemmer, et al. ∙

research

∙ 02/03/2023

Data Mesh: Motivational Factors, Challenges, and Best Practices

With the increasing importance of data and artificial intelligence, orga...

0 Jan Bode, et al. ∙

research

∙ 01/23/2023

Toward Foundation Models for Earth Monitoring: Generalizable Deep Learning Models for Natural Hazard Segmentation

Climate change results in an increased probability of extreme weather ev...

0 Johannes Jakubik, et al. ∙

research

∙ 12/22/2022

Data-centric Artificial Intelligence

Data-centric artificial intelligence (data-centric AI) represents an eme...

0 Johannes Jakubik, et al. ∙

research

∙ 09/22/2022

Deep Domain Adaptation for Detecting Bomb Craters in Aerial Images

The aftermath of air raids can still be seen for decades after the devas...

0 Marco Geiger, et al. ∙

research

∙ 08/08/2022

An Empirical Evaluation of Predicted Outcomes as Explanations in Human-AI Decision-Making

In this work, we empirically examine human-AI decision-making in the pre...

0 Johannes Jakubik, et al. ∙

research

∙ 07/01/2022

Training Novices: The Role of Human-AI Collaboration and Knowledge Transfer

Across a multitude of work environments, expert knowledge is imperative ...

0 Philipp Spitzer, et al. ∙

research

∙ 05/10/2022

A Meta-Analysis of the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making

Research in artificial intelligence (AI)-assisted decision-making is exp...

0 Max Schemmer, et al. ∙

research

∙ 05/04/2022

Machine Learning Operations (MLOps): Overview, Definition, and Architecture

The final goal of all industrial machine learning (ML) projects is to de...

0 Dominik Kreuzberger, et al. ∙

research

∙ 05/03/2022

On the Effect of Information Asymmetry in Human-AI Teams

Over the last years, the rising capabilities of artificial intelligence ...

0 Patrick Hemmer, et al. ∙

research

∙ 04/19/2022

Factors that influence the adoption of human-AI collaboration in clinical decision-making

Recent developments in Artificial Intelligence (AI) have fueled the emer...

0 Patrick Hemmer, et al. ∙

research

∙ 04/19/2022

On the Influence of Explainable AI on Automation Bias

Artificial intelligence (AI) is gaining momentum, and its importance for...

0 Max Schemmer, et al. ∙

research

∙ 04/14/2022

Should I Follow AI-based Advice? Measuring Appropriate Reliance in Human-AI Decision-Making

Many important decisions in daily life are made with the help of advisor...

0 Max Schemmer, et al. ∙

research

∙ 02/14/2022

Discrete Adjoint Momentum-Weighted Interpolation Strategies

This Technical Note outlines an adjoint complement to a critical buildin...

0 Niklas Kühl, et al. ∙

research

∙ 10/18/2021

Utilizing Active Machine Learning for Quality Assurance: A Case Study of Virtual Car Renderings in the Automotive Industry

Computer-generated imagery of car models has become an indispensable par...

0 Patrick Hemmer, et al. ∙

research

∙ 09/28/2021

Intelligent Decision Assistance Versus Automated Decision-Making: Enhancing Knowledge Work Through Explainable Artificial Intelligence

While recent advances in AI-based automated decision-making have shown m...

0 Max Schemmer, et al. ∙

research

∙ 09/28/2021

What to Prioritize? Natural Language Processing for the Development of a Modern Bug Tracking Solution in Hardware Development

Managing large numbers of incoming bug reports and finding the most crit...

0 Thi Thu Hang Do, et al. ∙

research

∙ 09/23/2021

Deep Learning Strategies for Industrial Surface Defect Detection Systems

Deep learning methods have proven to outperform traditional computer vis...

120 Dominik Martin, et al. ∙

research

∙ 09/21/2021

Fake or Credible? Towards Designing Services to Support Users' Credibility Assessment of News Content

Fake news has become omnipresent in digitalized areas such as social med...

0 Enrico Bunde, et al. ∙

research

∙ 09/02/2021

Towards a Reference Architecture for Future Industrial Internet of Things Networks

With the continuing decrease of sensor technology prices as well as the ...

0 Dominik Martin, et al. ∙

research

∙ 07/05/2021

Detecting Concept Drift With Neural Network Model Uncertainty

Deployed machine learning models are confronted with the problem of chan...

0 Lucas Baier, et al. ∙

research

∙ 04/23/2021

A Picture is Worth a Collaboration: Accumulating Design Knowledge for Computer-Vision-based Hybrid Intelligence Systems

Computer vision (CV) techniques try to mimic human capabilities of visua...

0 Patrick Zschech, et al. ∙

research

∙ 03/26/2021

A Novel p-Harmonic Descent Approach Applied to Fluid Dynamic Shape Optimization

We introduce a novel method for the implementation of shape optimziation...

0 Peter Marvin Müller, et al. ∙

research

∙ 03/05/2021

labelCloud: A Lightweight Domain-Independent Labeling Tool for 3D Object Detection in Point Clouds

Within the past decade, the rise of applications based on artificial int...

17 Christoph Sager, et al. ∙

research

∙ 01/14/2021

Needmining: Designing Digital Support to Elicit Needs from Social Media

Today's businesses face a high pressure to innovate in order to succeed ...

0 Niklas Kühl, et al. ∙

research

∙ 12/04/2020

Utilizing Concept Drift for Measuring the Effectiveness of Policy Interventions: The Case of the COVID-19 Pandemic

As a reaction to the high infectiousness and lethality of the COVID-19 v...

0 Lucas Baier, et al. ∙

research

∙ 11/30/2020

Human vs. supervised machine learning: Who learns patterns faster?

The capabilities of supervised machine learning (SML), especially compar...

0 Niklas Kühl, et al. ∙

research

∙ 11/05/2020

Switching Scheme: A Novel Approach for Handling Incremental Concept Drift in Real-World Data Sets

Machine learning models nowadays play a crucial role for many applicatio...

0 Lucas Baier, et al. ∙

research

∙ 10/20/2020

"Healthy surveillance": Designing a concept for privacy-preserving mask recognition AI in the age of pandemics

The obligation to wear masks in times of pandemics reduces the risk of s...

0 Niklas Kühl, et al. ∙

research

∙ 07/24/2020

Towards Leveraging End-of-Life Tools as an Asset: Value Co-Creation based on Deep Learning in the Machining Industry

Sustainability is the key concept in the management of products that rea...

0 Jannis Walk, et al. ∙

research

∙ 07/22/2020

DEAL: Deep Evidential Active Learning for Image Classification

Convolutional Neural Networks (CNNs) have proven to be state-of-the-art ...

0 Patrick Hemmer, et al. ∙

research

∙ 07/14/2020

An Uncertainty-based Human-in-the-loop System for Industrial Tool Wear Analysis

Convolutional neural networks have shown to achieve superior performance...

0 Alexander Treiss, et al. ∙

research

∙ 05/29/2020

AI-based Resource Allocation: Reinforcement Learning for Adaptive Auto-scaling in Serverless Environments

Serverless computing has emerged as a compelling new paradigm of cloud c...

0 Lucia Schuler, et al. ∙

research

∙ 05/15/2020

How to Learn from Others: Transfer Machine Learning with Additive Regression Models to Improve Sales Forecasting

In a variety of business situations, the introduction or improvement of ...

0 Robin Hirt, et al. ∙

research

∙ 05/13/2020

A network-based transfer learning approach to improve sales forecasting of new products

Data-driven methods – such as machine learning and time series forecasti...

0 Tristan Karb, et al. ∙

research

∙ 05/12/2020

Handling Concept Drift for Predictions in Business Process Mining

Predictive services nowadays play an important role across all business ...

0 Lucas Baier, et al. ∙

research

∙ 04/22/2020

A New Metric for Lumpy and Intermittent Demand Forecasts: Stock-keeping-oriented Prediction Error Costs

Forecasts of product demand are essential for short- and long-term optim...

0 Dominik Martin, et al. ∙

research

∙ 04/01/2020

Handling Concept Drifts in Regression Problems – the Error Intersection Approach

Machine learning models are omnipresent for predictions on big data. One...

0 Lucas Baier, et al. ∙

research

∙ 03/30/2020

Half-empty or half-full? A Hybrid Approach to Predict Recycling Behavior of Consumers to Increase Reverse Vending Machine Uptime

Reverse Vending Machines (RVMs) are a proven instrument for facilitating...

0 Jannis Walk, et al. ∙

research

∙ 03/29/2020

Sequential Transfer Machine Learning in Networks: Measuring the Impact of Data and Neural Net Similarity on Transferability

In networks of independent entities that face similar predictive tasks, ...

4 Robin Hirt, et al. ∙

Niklas Kühl

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