PUMA publications for /tag/Learning%20Machine

InfiniTouch: Finger-Aware Interaction on Fully Touch Sensitive Smartphones

visus — 2026-04-22T18:03:14+02:00

H. Le, S. Mayer, und N. Henze. (2018)InfiniTouch: Finger-Aware Interaction on Fully Touch Sensitive Smartphones.Proceedings of the 31th Annual ACM Symposium on User Interface Software and Technology, New York, NY, USA, ACM, [PUMA: vis(us) learning machine interaction touchscreen finger-aware vis-sks vis visus:henzens visus:mayersn visus:lehy tiger-generation:639124705458569286] URL

PalmTouch: Using the Palm As an Additional Input Modality on Commodity Smartphones

visus — 2026-04-22T18:03:13+02:00

H. Le, T. Kosch, P. Bader, S. Mayer, und N. Henze. (2018)PalmTouch: Using the Palm As an Additional Input Modality on Commodity Smartphones.Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Seite 360:1-360:13. New York, NY, USA, ACM, [PUMA: vis-sks vis vis(us) capacitive machine learning smartphone image palm visus:lehy visus:baderpk visus:koschts visus:mayersn visus:henzens tiger-generation:639124705458569286] URL

Demonstrating PalmTouch: The Palm as An Additional Input Modality on Commodity Smartphones

visus — 2026-04-22T18:03:13+02:00

H. Le, S. Mayer, T. Kosch, und N. Henze. (2018)Demonstrating PalmTouch: The Palm as An Additional Input Modality on Commodity Smartphones.Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, New York, NY, USA, ACM, [PUMA: vis(us) palm smartphone image learning machine capacitive vis-sks vis visus:koschts visus:henzens visus:mayersn visus:lehy tiger-generation:639124705458569286] URL

Real-Time Forecasting of Electricity Prices in Day-Ahead and Intraday-Auction Markets Using Statistical and Machine Learning Approaches

annettegugel — 2026-02-09T11:45:09+01:00

H. Wissel, N. Spanca, und K. Rudion. (2025)Real-Time Forecasting of Electricity Prices in Day-Ahead and Intraday-Auction Markets Using Statistical and Machine Learning Approaches. [PUMA: Approaches Day-Ahead Electricity Forecasting Intraday-Auction Learning Machine Markets Prices Real-Time Statistical Using and in of]

Appropriate data density models in probabilistic machine learning approaches for data analysis

mohannazadeh — 2026-01-21T10:36:02+01:00

T. Villmann, M. Kaden, M. Mohannazadeh Bakhtiari, und A. Villmann. (2019)Appropriate data density models in probabilistic machine learning approaches for data analysis.International Conference on Artificial Intelligence and Soft Computing, Seite 443--454. [PUMA: data density learning machine probabilistic]

FlectoLine: eine adaptive Fassade für nachhaltige Architektur FlectoLine: A responsive Façade for sustainable architecture

itft-puma — 2025-10-07T14:17:51+02:00

A. Körner, E. Martin, L. Born, M. Ridder, S. Moser, R. Weitlaner, G. Gresser, und J. Knippers. (Oktober 2025)FlectoLine: eine adaptive Fassade für nachhaltige Architektur FlectoLine: A responsive Façade for sustainable architecture.Stahlbau, [PUMA: Aktuatorik Bionik Fassade Kunststoff Lernen Mechanismen Photovoltaik Zwilling actuation adaptive biomimetic compliant digital digitaler faserverstärkter façade fibre learning machine maschinelles mechanisms nachgiebige photo plastic pneumatic pneumatische reinforced responsive twin voltaic] URL

Optimal information injection and transfer mechanisms for active matter reservoir computing

mgaimann — 2025-09-10T16:49:59+02:00

M. Gaimann, und M. Klopotek. (2025)Optimal information injection and transfer mechanisms for active matter reservoir computing.arXiv, [PUMA: (cond-mat.soft), (cs.LG), (nlin.AO), (physics.comp-ph), Adaptation Computational Computer Condensed FOS: Learning Machine Matter Physical Physics Self-Organizing Soft Systems and information manybodyml myown publist sciences sciences,] URL

Robustly optimal dynamics for active matter reservoir computing

mgaimann — 2025-09-10T16:49:59+02:00

M. Gaimann, und M. Klopotek. (2025)Robustly optimal dynamics for active matter reservoir computing.arXiv, [PUMA: (cond-mat.soft), (cs.LG), (nlin.AO), (physics.comp-ph), Adaptation Computational Computer Condensed FOS: Learning Machine Matter Physical Physics Self-Organizing Soft Systems and information manybodyml myown publist sciences sciences,] URL

Quantification of training‐induced alterations in body composition via automated machine learning analysis of MRI images in the thigh region: A pilot study in young females

inspo5 — 2025-01-31T11:03:06+01:00

S. Ramedani, E. Kelesoglu, N. Stutzig, H. Von Tengg‐Kobligk, K. Daneshvar Ghorbani, und T. Siebert. (Januar 2025)Quantification of training‐induced alterations in body composition via automated machine learning analysis of MRI images in the thigh region: A pilot study in young females.Physiological Reports, Volume 13. Wiley, [PUMA: body composition deep imaging learning machine magnetic medicine musculoskeletal resonance sports system] URL

InfiniTouch: Finger-Aware Interaction on Fully Touch Sensitive Smartphones

tiger — 2024-11-29T10:42:09+01:00

H. Le, S. Mayer, und N. Henze. (2018)InfiniTouch: Finger-Aware Interaction on Fully Touch Sensitive Smartphones.Proceedings of the 31th Annual ACM Symposium on User Interface Software and Technology, New York, NY, USA, ACM, [PUMA: vis(us) interaction learning machine touchscreen finger-aware vis-sks vis visus:henzens visus:mayersn visus:lehy tiger-generation:638684700229105045] URL

PalmTouch: Using the Palm As an Additional Input Modality on Commodity Smartphones

tiger — 2024-11-29T10:42:07+01:00

H. Le, T. Kosch, P. Bader, S. Mayer, und N. Henze. (2018)PalmTouch: Using the Palm As an Additional Input Modality on Commodity Smartphones.Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Seite 360:1-360:13. New York, NY, USA, ACM, [PUMA: vis-sks vis vis(us) smartphone image machine learning palm capacitive visus:lehy visus:baderpk visus:koschts visus:mayersn visus:henzens tiger-generation:638684700229105045] URL

Demonstrating PalmTouch: The Palm as An Additional Input Modality on Commodity Smartphones

tiger — 2024-11-29T10:42:04+01:00

H. Le, S. Mayer, T. Kosch, und N. Henze. (2018)Demonstrating PalmTouch: The Palm as An Additional Input Modality on Commodity Smartphones.Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, New York, NY, USA, ACM, [PUMA: vis(us) palm smartphone image learning machine capacitive vis-sks vis visus:henzens visus:mayersn visus:koschts visus:lehy tiger-generation:638684700229105045] URL

Learning Compensation of the State-Dependent Transmission Errors in Rack-and-Pinion Drives

isw-bibliothek — 2024-07-26T11:59:23+02:00

L. Steinle, V. Leipe, A. Lechler, und A. Veri. (Juni 2024)Learning Compensation of the State-Dependent Transmission Errors in Rack-and-Pinion Drives.2024 European Control Conference (ECC), Seite 2441-2447. [PUMA: compensation drive error feed isw learning machine tool]

LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching

hominhduynguyen — 2024-02-19T14:41:03+01:00

D. Minh Ho Nguyen, H. Nguyen, N. T Diep, T. N Pham, T. Cao, B. T Nguyen, P. Swoboda, N. Ho, S. Albarqouni, P. Xie und 2 andere Autor(en). (2023)LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching.Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS 2023), [PUMA: graph; learning machine] URL

Tool condition monitoring in drilling processes using anomaly detection approaches based on control internal data

treeber — 2024-02-02T08:07:58+01:00

T. Reeber, J. Henninger, N. Weingarz, P. Simon, M. Berndt, M. Glatt, B. Kirsch, R. Eisseler, J. Aurich, und H. Möhring. (2024)Tool condition monitoring in drilling processes using anomaly detection approaches based on control internal data.Procedia CIRP, Volume 121. Seite 216–221. Elsevier BV, [PUMA: analysis anomaly condition detection learning machine machining manufacturing monitoring networks neural process series time tool] URL

Adaptive compensation of the transmission errors in rack-and-pinion drives

isw-bibliothek — 2022-08-09T08:52:30+02:00

A. Verl, und L. Steinle. (2022)Adaptive compensation of the transmission errors in rack-and-pinion drives.CIRP Annals, Volume 71. Seite 345--348. Elsevier BV, [PUMA: Compensation Feed Learning Machine drive tool] URL

Post-Anthropocene: The Design after the Human Centered Design Age

mariedavidova — 2022-01-20T14:39:51+01:00

M. Davidová, und Y. Zavoleas. (2020)Post-Anthropocene: The Design after the Human Centered Design Age.CAADRIA 2020: Re:Anthropocene - Design in the Age of Humans, Seite 203-212. Association for Computer Aided Architectural Design in Asia, [PUMA: approach architetural biodiversity learning machine morre-than-human myown performance post-Anthropocene systemic to urban] URL

Spiralling Slope as a Real Life Co-Design Laboratory

mariedavidova — 2022-01-19T17:25:49+01:00

M. Davidová, K. Pánek, und M. Pánková. (2018)Spiralling Slope as a Real Life Co-Design Laboratory.Seite 133-142. University of Arizona, [PUMA: biodiversity codesign ecosystem gigamapping learning life machine myown performance] URL

sysloop

mariedavidova — 2022-01-19T17:21:39+01:00

K. Pánek, und M. Davidová. (2018)sysloop.Seite 132-141. University of Arizona, [PUMA: architecture codesign intelligent learning machine myown responsive systems] URL

CataNet: Predicting remaining cataract surgery duration

felixholm — 2021-08-08T00:02:03+02:00

A. Marafioti, M. Hayoz, M. Gallardo, P. Neila, S. Wolf, M. Zinkernagel, und R. Sznitman. (2021)CataNet: Predicting remaining cataract surgery duration.MICCAI 2021, [PUMA: cataract duration learning machine prediction surgery] URL