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Employing Hybrid AI Systems to Trace and Document Bias in ML Pipelines
A hybrid AI system capable of identifying bias patterns in datasets used by predictive AI models. The proposed system captures knowledge about dataset characteristics and... -
Leibniz University Hannover
Imported
Z+F Imager 5016 Distance Uncertainty
This dataset presents a comparative analysis between a high accurate reference point cloud acquired using the Leica ATR 960 (Laser tracker) and Leica LAS XL (Hand-held scanner),... -
RADAR (Research Data Repository)
Imported
Experimental data for the paper "a comprehensive study of k-portfolios of rec...
Abstract: These are the experimental data for the paper Bach, Jakob, Markus Iser, and Klemens Böhm. "A Comprehensive Study of k-Portfolios of Recent SAT Solvers" published at... -
RADAR (Research Data Repository)
Imported
Experimental data for the paper "analyzing and predicting verification of dat...
Abstract: These are the experimental data for the paper Ordoni, Elaheh, Jakob Bach, and Ann-Katrin Fleck. "Analyzing and Predicting Verification of Data-Aware Process Models--A... -
RADAR (Research Data Repository)
Imported
Datasets for "uncovering developmental time and tempo using deep learning"
Abstract: This is the data repository for training and testing the Twin Network. The imaging data repositories are divided into several packages based on independent... -
RADAR (Research Data Repository)
Imported
Datasets for "embryonet: using deep learning to link embryonic phenotypes to ...
Abstract: This is the data repository of the training and test data sets for EmbryoNet. The data is structured in multiple packages. EmbryoNet_Models (DOI 10.48606/31) contains... -
RADAR (Research Data Repository)
Imported
A neural operator-based surrogate solver for free-form electromagnetic invers...
This dataset has no description
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Leibniz University Hannover
Imported
A Neural Approach for Text Extraction from Scholarly Figures
A Neural Approach for Text Extraction from Scholarly Figures This is the readme for the supplemental data for our ICDAR 2019 paper. You can read our paper via IEEE here:...