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New paper at the Interactive Adaptive Learning (IAL) Workshop, ECML PKDD 2023
The article "Who knows best? A Case Study on Intelligent Crowdworker Selection via Deep Learning" by Marek Herde, Denis Huseljic, Bernhard Sick, Ulrich Bretschneider and Sarah Oeste-Reiß presents a case study demonstrating how the application of deep learning for intelligent crowdworker selection reduces the number of erroneous annotations and thus reduces the annotation costs for creating reliable training data for deep neural networks.
News
New paper at the Interactive Adaptive Learning (IAL) Workshop, ECML PKDD 2023
The article "Who knows best? A Case Study on Intelligent Crowdworker Selection via Deep Learning" by Marek Herde, Denis Huseljic, Bernhard Sick, Ulrich Bretschneider and Sarah Oeste-Reiß presents a case study demonstrating how the application of deep learning for intelligent crowdworker selection reduces the number of erroneous annotations and thus reduces the annotation costs for creating reliable training data for deep neural networks.
Dates
New paper at the Interactive Adaptive Learning (IAL) Workshop, ECML PKDD 2023
The article "Who knows best? A Case Study on Intelligent Crowdworker Selection via Deep Learning" by Marek Herde, Denis Huseljic, Bernhard Sick, Ulrich Bretschneider and Sarah Oeste-Reiß presents a case study demonstrating how the application of deep learning for intelligent crowdworker selection reduces the number of erroneous annotations and thus reduces the annotation costs for creating reliable training data for deep neural networks.