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On the Effect of Contextual Information on Human Delegation Behavior in Human-AI collaboration
In this work, we explore the effects of providing contextual information on human decisions to delegate instances to an AI.
Enabling Inter-organizational Analytics in Business Networks Through Meta Machine Learning
While it is often feasible to generate larger data pools within organizations, the application of analytics within (inter-organizational) business networks is still severely constrained.
Deep Domain Adaptation for Detecting Bomb Craters in Aerial Images
The current manual analysis process is expensive and time-consuming, thus automated detection of bomb craters by using deep learning is a promising way to improve the UXO disposal process.
Deep Learning Strategies for Industrial Surface Defect Detection Systems
Deep learning methods have proven to outperform traditional computer vision methods in various areas of image processing.
Human vs. supervised machine learning: Who learns patterns faster?
We have designed an experiment in which 44 humans and three different machine learning algorithms identify patterns in labeled training data and have to label instances according to the patterns they find.
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 optimization of logistics and production.
