tag :: machine

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publications (hide)34
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1Chapter 5 - Artificial intelligence (AI) enhanced nanomotors and active matter
F. Cichos, S. Landin, and R. Pradip. Intelligent Nanotechnology, Elsevier, (2023)
2 months ago by @scadsfct
show all tags
topic_physchemistry
Active
Feedback
Machine
Multi
Optical
Reinforcement
agent
control
control,
learning,
particles,
reinforcement
topic_physchemistryActiveFeedbackMachineMultiOpticalReinforcementagentcontrolcontrol,learning,particles,reinforcement
(0)
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1Stability selection enables robust learning of partial differential equations from limited noisy data
S. Maddu, B. Cheeseman, I. Sbalzarini, and C. Müller. (2019)
2 months ago by @scadsfct
show all tags
(cs.LG),
(math.NA),
(physics.data-an),
Analysis
Analysis,
Computer
Data
FOS:
Learning
Machine
Mathematics,
Numerical
Physical
Probability
Statistics
and
information
sciences
sciences,
(cs.LG),(math.NA),(physics.data-an),AnalysisAnalysis,ComputerDataFOS:LearningMachineMathematics,NumericalPhysicalProbabilityStatisticsandinformationsciencessciences,
(0)
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2Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning
L. Lange, M. Heykeroth, and E. Rahm. arXiv preprint arXiv:2409.01329, (September 2024)
13 days ago by @scadsfct
show all tags
area_responsibleai
area_bigdata
(cs.CR),
(cs.CV),
(cs.LG),
Computer
Cryptography
FOS:
Learning
Machine
Pattern
Recognition
Security
Vision
and
ep
information
sciences
area_responsibleaiarea_bigdata(cs.CR),(cs.CV),(cs.LG),ComputerCryptographyFOS:LearningMachinePatternRecognitionSecurityVisionandepinformationsciences
(0)
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1A methodology for direct parameter identification for experimental results using machine learning — Real world application to the highly non-linear deformation behavior of FRP
J. Gerritzen, A. Hornig, P. Winkler, and M. Gude. Computational Materials Science, (September 2024)Publisher Copyright: © 2024 The Author(s).
13 days ago by @scadsfct
show all tags
area_architectures
topic_engineering
Constitutive
FIS_scads
Fiber
Machine
Neural
Parameter
identification
learning,
modeling,
networks,
plastics,
reinforced
area_architecturestopic_engineeringConstitutiveFIS_scadsFiberMachineNeuralParameteridentificationlearning,modeling,networks,plastics,reinforced
(0)
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1Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning
J. Gerritzen, A. Hornig, P. Winkler, and M. Gude. ECCM21 - Proceedings of the 21st European Conference on Composite Materials, 3, page 1252--1259. European Society for Composite Materials (ESCM), (Jul 2, 2024)21st European Conference on Composite Materials, ECCM 21 ; Conference date: 02-07-2024 Through 05-07-2024.
13 days ago by @scadsfct
show all tags
area_architectures
topic_engineering
Convolutional
Direct
FIS_scads
Fiber
Machine
Strain
dependency,
identification,
learning,
networks,
neural
parameter
plastics
rate
reinforced
area_architecturestopic_engineeringConvolutionalDirectFIS_scadsFiberMachineStraindependency,identification,learning,networks,neuralparameterplasticsratereinforced
(0)
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1A comparative patient-level prediction study in OMOP CDM: applicative potential and insights from synthetic data
N. Ahmadi, {. Nguyen, M. Sedlmayr, and M. Wolfien. Scientific reports, (Jan 27, 2024)
13 days ago by @scadsfct
show all tags
Databases,
Electronic
FIS_scads
Factual,
Health
Humans,
Informatics,
Learning,
Machine
Medical
Records
topic_lifescience
Databases,ElectronicFIS_scadsFactual,HealthHumans,Informatics,Learning,MachineMedicalRecordstopic_lifescience
(0)
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1Towards Standardizing Ophthalmic Data for Seamless Interoperability in Eye Care
K. Hoffmann, Y. Peng, T. Schlosser, G. Stolze, H. Langner, M. Susky, T. Meyer, M. Ritter, D. Kowerko, V. Kakkassery and 2 other author(s). Studies in health technology and informatics, (Aug 30, 2024)Publisher Copyright: © 2024 The Authors..
13 days ago by @scadsfct
show all tags
topic_lifescience
Diseases/therapy,
Electronic
Eye
FIS_scads
Germany,
Health
Humans,
Information
Interoperability/standards,
Learning,
Level
Machine
Ophthalmology
Records/standards,
Seven/standards,
topic_lifescienceDiseases/therapy,ElectronicEyeFIS_scadsGermany,HealthHumans,InformationInteroperability/standards,Learning,LevelMachineOphthalmologyRecords/standards,Seven/standards,
(0)
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1CCR2 macrophage response determines the functional outcome following cardiomyocyte transplantation
P. Vasudevan, M. Wolfien, H. Lemcke, {. Lang, A. Skorska, R. Gaebel, A. Galow, D. Koczan, T. Lindner, W. Bergmann and 6 other author(s). Genome medicine, (Aug 10, 2023)Publisher Copyright: © 2023, BioMed Central Ltd., part of Springer Nature..
13 days ago by @scadsfct
show all tags
topic_lifescience
Animals,
C57BL,
Cardiac/metabolism,
Cell
FIS_scads
Immunocompromised,
Inbred
Infarction,
Machine
Macrophages,
Macrophages/metabolism,
Mice,
Monocytes/metabolism
Myocardial
Myocytes,
Single-cell,
infarction,
learning,
therapy,
topic_lifescienceAnimals,C57BL,Cardiac/metabolism,CellFIS_scadsImmunocompromised,InbredInfarction,MachineMacrophages,Macrophages/metabolism,Mice,Monocytes/metabolismMyocardialMyocytes,Single-cell,infarction,learning,therapy,
(0)
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1Stability selection enables robust learning of differential equations from limited noisy data
S. Maddu, {. Cheeseman, {. Sbalzarini, and {. Müller. Proceedings of the Royal Society of London : Series A, Mathematical, physical and engineering sciences, (June 2022)Publisher Copyright: © 2022 Royal Society Publishing. All rights reserved..
13 days ago by @scadsfct
show all tags
topic_lifescience
FIS_scads
PAR
differential
equations,
learning
learning,
machine
proteins,
regression,
selection,
sparse
stability
statistical
theory
topic_lifescienceFIS_scadsPARdifferentialequations,learninglearning,machineproteins,regression,selection,sparsestabilitystatisticaltheory
(0)
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1RTASS: a RunTime Adaptable and Scalable System for Network-on-Chip-Based Architectures
N. Charaf, J. Haase, A. Kulisch, {. Elm, and D. Göhringer. 2023 26th Euromicro Conference on Digital System Design (DSD), page 585--592. IEEE, (Sep 8, 2023)Publisher Copyright: © 2023 IEEE.; 26th Euromicro Conference on Digital System Design, DSD 2023 ; Conference date: 06-09-2023 Through 08-09-2023.
13 days ago by @scadsfct
show all tags
topic_federatedlearn
Computer
Embedded
FIS_scads
Machine
Runtime,
Scalability,
Shape
algorithms,
architecture,
computing,
learning
vision,
topic_federatedlearnComputerEmbeddedFIS_scadsMachineRuntime,Scalability,Shapealgorithms,architecture,computing,learningvision,
(0)
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1Data-driven determination of plant growth stages for improved weather index insurance design
J. Zou, M. Odening, and O. Okhrin. Agricultural Finance Review, (2024)Publisher Copyright: © 2024, Jing Zou, Martin Odening and Ostap Okhrin..
13 days ago by @scadsfct
show all tags
topic_engineering
FIS_scads
Generalized
Machine
Plant
Temporal
Weather
additive
basis
growth
index
insurance
learning,
model,
risk,
stages,
topic_engineeringFIS_scadsGeneralizedMachinePlantTemporalWeatheradditivebasisgrowthindexinsurancelearning,model,risk,stages,
(0)
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1Identifying Secondary School Students' Misconceptions about Machine Learning: An Interview Study
E. Marx, C. Witt, and T. Leonhardt. WiPSCE '24: Proceedings of the 19th WiPSCE Conference on Primary and Secondary Computing Education Research, page 1--10. Association for Computing Machinery, (Sep 16, 2024)Publisher Copyright: © 2024 Copyright held by the owner/author(s)..
13 days ago by @scadsfct
show all tags
area_responsibleai
FIS_scads
artificial
conceptions
intelligence,
interview
learning,
machine
mental
misconceptions,
models,
qualitative
research,
students
study,
area_responsibleaiFIS_scadsartificialconceptionsintelligence,interviewlearning,machinementalmisconceptions,models,qualitativeresearch,studentsstudy,
(0)
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1Brief Summary of Existing Research on Students’ Conceptions of AI
E. Marx, T. Leonhardt, and N. Bergner. (October 2022)Publisher Copyright: © 2022 Owner/Author.; WiPSCE 2022 ; Conference date: 31-10-2022 Through 02-11-2022.
13 days ago by @scadsfct
show all tags
area_responsibleai
FIS_scads
artificial
beliefs,
conceptions,
education,
ideas,
intelligence,
k-12
learning,
machine
mental
models,
preconceptions
area_responsibleaiFIS_scadsartificialbeliefs,conceptions,education,ideas,intelligence,k-12learning,machinementalmodels,preconceptions
(0)
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1Explainable Earth Surface Forecasting under Extreme Events
O. Pellicer-Valero, M. Fernández-Torres, C. Ji, M. Mahecha, and G. Camps-Valls. (2024)
8 days ago by @joum576e
show all tags
(cs.LG),
Computer
FOS:
Learning
Machine
and
information
sciences
sciences,
topic_earthenvironment
(cs.LG),ComputerFOS:LearningMachineandinformationsciencessciences,topic_earthenvironment
(0)
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2A Light-weight and Unsupervised Method for Near Real-time Behavioral Analysis using Operational Data Measurement
T. Vargis, and S. Ghiasvand. The International Conference for High Performance Computing, Networking, Storage, and Analysis, Dallas, Texas, USA, (January 2022)arXiv:2402.05114 cs.
a day ago by @ghiasvan
show all tags
Cluster
Computer
Computing,
Distributed,
Learning
Machine
Parallel,
Science
and
myOwn
ClusterComputerComputing,Distributed,LearningMachineParallel,ScienceandmyOwn
(0)
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2Content-Aware Depth-Adaptive Image Restoration
T. Vargis, and S. Ghiasvand. Proceedings of the 29th International Conference on Automation and Computing, Sunderland, UK, (January 2024)arXiv:2401.05049 cs.
a day ago by @ghiasvan
show all tags
Computer
Learning,
Machine
Pattern
Recognition,
Science
Vision
and
myOwn
ComputerLearning,MachinePatternRecognition,ScienceVisionandmyOwn
(0)
copydeleteadd this publication to your clipboard
2Content-Aware Depth-Adaptive Image Restoration
T. Vargis, and S. Ghiasvand. Proceedings of the 29th International Conference on Automation and Computing, Sunderland, UK, (January 2024)arXiv:2401.05049 cs.
a day ago by @scads.ai
show all tags
Learning,
myOwn
from:ghiasvan
and
Computer
Vision
Pattern
Machine
Recognition,
Science
Learning,myOwnfrom:ghiasvanandComputerVisionPatternMachineRecognition,Science
(0)
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2A Light-weight and Unsupervised Method for Near Real-time Behavioral Analysis using Operational Data Measurement
T. Vargis, and S. Ghiasvand. The International Conference for High Performance Computing, Networking, Storage, and Analysis, Dallas, Texas, USA, (January 2022)arXiv:2402.05114 cs.
a day ago by @scads.ai
show all tags
Parallel,
myOwn
from:ghiasvan
Learning
and
Computer
Cluster
Distributed,
Computing,
Machine
Science
Parallel,myOwnfrom:ghiasvanLearningandComputerClusterDistributed,Computing,MachineScience
(0)
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2Cloudy with a chance of precision: satellite’s autoconversion rates forecasting powered by machine learning
M. Novitasari, J. Quaas, and M. Rodrigues. Environmental Data Science, (2024)
a day ago by @scadsfct
show all tags
autoconversion
forecasting
learning
machine
rates
satellite
autoconversionforecastinglearningmachineratessatellite
(0)
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1Machine Learning Based Mobile Capacity Estimation for Roadside Parking
A. Kramm, E. Peukert, A. Ludwig, and B. Franczyk. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, (2024)
a day ago by @scadsfct
show all tags
Based
Capacity
Estimation
Learning
Machine
Mobile
Parking
Roadside
BasedCapacityEstimationLearningMachineMobileParkingRoadside
(0)
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publications (hide)34
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1Chapter 5 - Artificial intelligence (AI) enhanced nanomotors and active matter

1Stability selection enables robust learning of partial differential equations from limited noisy data

2Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning

1A methodology for direct parameter identification for experimental results using machine learning — Real world application to the highly non-linear deformation behavior of FRP

1Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning

1A comparative patient-level prediction study in OMOP CDM: applicative potential and insights from synthetic data

1Towards Standardizing Ophthalmic Data for Seamless Interoperability in Eye Care

1CCR2 macrophage response determines the functional outcome following cardiomyocyte transplantation

1Stability selection enables robust learning of differential equations from limited noisy data

1RTASS: a RunTime Adaptable and Scalable System for Network-on-Chip-Based Architectures

1Data-driven determination of plant growth stages for improved weather index insurance design

1Identifying Secondary School Students' Misconceptions about Machine Learning: An Interview Study

1Brief Summary of Existing Research on Students’ Conceptions of AI

1Explainable Earth Surface Forecasting under Extreme Events

2A Light-weight and Unsupervised Method for Near Real-time Behavioral Analysis using Operational Data Measurement

2Content-Aware Depth-Adaptive Image Restoration

2Content-Aware Depth-Adaptive Image Restoration

2A Light-weight and Unsupervised Method for Near Real-time Behavioral Analysis using Operational Data Measurement

2Cloudy with a chance of precision: satellite’s autoconversion rates forecasting powered by machine learning

1Machine Learning Based Mobile Capacity Estimation for Roadside Parking

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