TmoTA: Simple, Highly Responsive Tool for Multiple Object Tracking Annotation. In Albrecht Schmidt, Kaisa Väänänen, EditoTesh Goyal, Per Ola Kristensson, Anicia Peters, Stefanie Mueller, Julie R. Williamson, und Max L. Wilson (Hrsg.), CHI 2023 - Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, 19.04.2023. [PUMA: topic_visualcomputing FIS_scads data labeling labeling, manual sequence video] URL
PEARL: Physical Environment based Augmented Reality Lenses for In-Situ Human Movement Analysis. CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 19.04.2023. [PUMA: topic_visualcomputing Analytics, FIS_scads Immersive In-situ affordance, analysis, augmented/mixed data movement physical reality, referents, visualization]
ConvGeN: A convex space learning approach for deep-generative oversampling and imbalanced classification of small tabular datasets. Pattern recognition : the journal of the Pattern Recognition Society, (147)Elsevier Science B.V., März 2024. [PUMA: topic_lifescience Convex FIS_scads GAN, Imbalanced LoRAS, Tabular data data, learning, space]
Parallel Discrete Convolutions on Adaptive Particle Representations of Images. IEEE Transactions on Image Processing, (31):4197--4212, Wiley-IEEE Press, 01.01.2022. [PUMA: topic_lifescience Convolution, Data FIS_scads Image Microscopy, Signal processing, reconstruction, resolution resolution, structures,]
Graph based process models as basis for efficient data driven surrogates - Expediting the material development process. engrXiv : engineering archive, Open Engineering Inc., 16.11.2024. [PUMA: topic_engineering Data FIS_scads Process Surrogate decision development, driven making modeling,]
Assessing Anonymized System Logs Usefulness for Behavioral Analysis in RNN Models. CEUR Workshop Proceedings, (3376)RTWH Aachen, 02.12.2022. [PUMA: livinglab Data FIS_scads System Time analysis analysis, log series usefulness,]
A standardized clinical data harmonization pipeline for scalable ai application deployment (fhir-dhp): Validation and usability study. JMIR Medical Informatics, (11):e43847, JMIR Publications Toronto, Canada, 2023. [PUMA: topic_neuroinspired (fhir-dhp) ai application clinical data deployment harmonization pipeline scalable standardized]
A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters. Journal of Composites Science, (6)10:318, MDPI, 2022. [PUMA: topic_engineering 3D Approach Characterisation Composites Data Deformation Dependent Driven Experimental Failure Fibre Modelling Rate Reinforced Shear Strain Thermoplastic]
Breaking Barriers: Workshop on Open Data Practices in AutoUI Research. Adjunct Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 227--230, 2023. [PUMA: topic_visualcomputing AutoUI Data Open Practices Research Workshop]
Exploring Millions of User Interactions with ICEBOAT: Big Data Analytics for Automotive User Interfaces. Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 81--92, 2023. [PUMA: topic_visualcomputing Analytics Automotive Big Data ICEBOAT Interactions Interfaces User]
Destination Prediction Based on Partial Trajectory Data. 2020. [PUMA: Based Data Destination Partial Prediction Trajectory on] URL
ICEBOAT: An Interactive User Behavior Analysis Tool for Automotive User Interfaces. Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology, Association for Computing Machinery, New York, NY, USA, 2022. [PUMA: topic_visualcomputing Data Design Driving Human-Computer In-Vehicle Information Interaction Naturalistic System Tools Visualization] URL
Stability selection enables robust learning of partial differential equations from limited noisy data. arXiv, 2019. [PUMA: (cs.LG), (math.NA), (physics.data-an), Analysis Analysis, Computer Data FOS: Learning Machine Mathematics, Numerical Physical Probability Statistics and information sciences sciences,] URL
Graph Mining for Complex Data Analytics. 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), 1316--1319, Dezember 2016. [PUMA: Data Intelligence Mining;Business algorithms;Conferences;Graph analysis;Data and design mining;Business;Algorithm models;Libraries;Partitioning]
Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction. JHEP Rep., (4)4:100443, Elsevier BV, April 2022. [PUMA: topic_lifescience AI, Artificial CNN, Communications DICOM, Diagnosis; Digital HCC, Imaging Individual ML, MVI, Medicine; NAFLD, NASH, Prognosis Reporting TACE, TRIPOD, Transparent WSIs, a and artificial carcinoma; chemoembolisation; convolutional data deep diagnostic disease; fatty for hepatocellular images; imaging; in integration intelligence; invasion; learning; liver machine microvascular model multimodal multivariable network; neural non-alcoholic of or prediction slide steatohepatitis; support system; transarterial whole]
Multi-source dataset of e-commerce products with attributes for property matching. Data Brief, (41)107884:107884, Elsevier BV, April 2022. [PUMA: area_bigdata integration; engineering; Data Ontology; Property matching]
Automated algorithm selection: Survey and perspectives. Evol. Comput., (27)1:3--45, MIT Press, 2019. [PUMA: Automated algorithm analysis; approaches; automated combinatorial configuration; continuous data exploratory feature-based landscape learning; machine metalearning optimisation; selection; streams.;]
Toward Veracity Assessment in RDF Knowledge Bases: An Exploratory Analysis. J. Data and Information Quality, (9)3Association for Computing Machinery, New York, NY, USA, Februar 2018. [PUMA: DeFacto, analysis benchmark, checking, data data, exploratory fact linked quality, trustworthiness,] URL
Integration of mathematical model predictions into routine workflows to support clinical decision making in haematology. BMC Med. Inform. Decis. Mak., (20)1:28, Februar 2020. [PUMA: Clinical Computer Data Haematology; Individual Mathematical Model-based Routine Support decision-making; management; modelling; optimization; planning; simulation; system therapy treatment workflow;]
Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis. Gigascience, (13)Januar 2024. [PUMA: topic_federatedlearn AutoML; analysis; classification data learning; machine problems; visualization]