scadsfct > machine

Lesezeichen (verstecken)
Anzeige
alles
nur Lesezeichen
Lesezeichen pro Seite
5
10
20
50
100
sortieren nach
hinzugefügt am
Titel
RSS
BibTeX
XML

Keine Treffer.

⟨⟨
⟨
⟩
⟩⟩

Publikationen (verstecken)33
Anzeige
alles
nur Publikationen
Publikationen pro Seite
5
10
20
50
100
sortieren nach
hinzugefügt am
Titel
Autor
Erscheinungsdatum
Eintragstyp
Hilfe für erweiterte Sortierung...
RSS
BibTeX
RDF
mehr...

1MLcps: machine learning cumulative performance score for classification problems
A. Akshay, M. Abedi, N. Shekarchizadeh, F. Burkhard, M. Katoch, A. Bigger-Allen, R. Adam, K. Monastyrskaya, und A. Gheinani. GigaScience, (Dezember 2023)
vor einem Monat von @scadsfct
alle anzeigen
MLcps
Xack
Yaff
cumulative
learning
machine
performance
MLcpsXackYaffcumulativelearningmachineperformance
(0)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1Cost-Sensitive Best Subset Selection for Logistic Regression: A Mixed-Integer Conic Optimization Perspective
R. Knauer, und E. Rodner. KI 2023: Advances in Artificial Intelligence: 46th German Conference on AI, Berlin, Germany, September 26--29, 2023, Proceedings, Seite 114--129. Berlin, Heidelberg, Springer-Verlag, (2023)
vor einem Monat von @scadsfct
alle anzeigen
Zno
best
conic
cost-sensitive
interpretable
learning
machine
meta-learning
mixed-integer
optimization
selection
subset
Znobestconiccost-sensitiveinterpretablelearningmachinemeta-learningmixed-integeroptimizationselectionsubset
(0)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1Extendable hybrid approach to detect conscious states in a CLIS patient using machine learning
S. Adama, S. Wu, N. Nicolaou, und M. Bogdan. SNE Simul. Notes Eur., 32 (1): 37--45 (2022)
vor einem Monat von @scadsfct
alle anzeigen
Zno
conscious
hybrid
learning
machine
patient
states
{CLIS}
Znoconscioushybridlearningmachinepatientstates{CLIS}
(0)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
2Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient
O. Kirsten, M. Bogdan, und S. Adama. 2023 7th International Conference on Imaging, Signal Processing and Communications (ICISPC), Seite 37-41. (2023)
vor einem Monat von @scadsfct
alle anzeigen
Complexity
Computational
Consciousness
Information
Learning
Locked-In
Machine
Measures
Modeling
Neuroscience
Prediction
Predictive
Processing
Signal
Syndrome
Theory
Training
Zno
algorithms
and
data
learning
modeling
models
processing
ComplexityComputationalConsciousnessInformationLearningLocked-InMachineMeasuresModelingNeurosciencePredictionPredictiveProcessingSignalSyndromeTheoryTrainingZnoalgorithmsanddatalearningmodelingmodelsprocessing
(0)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1Machine Learning Based Mobile Capacity Estimation for Roadside Parking
A. Kramm, E. Peukert, A. Ludwig, und B. Franczyk. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, (2024)
vor 2 Monaten von @scadsfct
alle anzeigen
Based
Capacity
Estimation
Learning
Machine
Mobile
Parking
Roadside
BasedCapacityEstimationLearningMachineMobileParkingRoadside
(0)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
2Cloudy with a chance of precision: satellite’s autoconversion rates forecasting powered by machine learning
M. Novitasari, J. Quaas, und M. Rodrigues. Environmental Data Science, (2024)
vor 2 Monaten von @scadsfct
alle anzeigen
autoconversion
forecasting
learning
machine
rates
satellite
autoconversionforecastinglearningmachineratessatellite
(0)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
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, und M. Gude. Computational Materials Science, (September 2024)Publisher Copyright: © 2024 The Author(s).
vor 2 Monaten von @scadsfct
alle anzeigen
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)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning
J. Gerritzen, A. Hornig, P. Winkler, und M. Gude. ECCM21 - Proceedings of the 21st European Conference on Composite Materials, 3, Seite 1252--1259. European Society for Composite Materials (ESCM), (02.07.2024)21st European Conference on Composite Materials, ECCM 21 ; Conference date: 02-07-2024 Through 05-07-2024.
vor 2 Monaten von @scadsfct
alle anzeigen
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)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1A comparative patient-level prediction study in OMOP CDM: applicative potential and insights from synthetic data
N. Ahmadi, {. Nguyen, M. Sedlmayr, und M. Wolfien. Scientific reports, (27.01.2024)
vor 2 Monaten von @scadsfct
alle anzeigen
Databases,
Electronic
FIS_scads
Factual,
Health
Humans,
Informatics,
Learning,
Machine
Medical
Records
topic_lifescience
Databases,ElectronicFIS_scadsFactual,HealthHumans,Informatics,Learning,MachineMedicalRecordstopic_lifescience
(0)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
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 und 2 andere Autor(en). Studies in health technology and informatics, (30.08.2024)Publisher Copyright: © 2024 The Authors..
vor 2 Monaten von @scadsfct
alle anzeigen
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)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
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 und 6 andere Autor(en). Genome medicine, (10.08.2023)Publisher Copyright: © 2023, BioMed Central Ltd., part of Springer Nature..
vor 2 Monaten von @scadsfct
alle anzeigen
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)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1Stability selection enables robust learning of differential equations from limited noisy data
S. Maddu, {. Cheeseman, {. Sbalzarini, und {. Müller. Proceedings of the Royal Society of London : Series A, Mathematical, physical and engineering sciences, (Juni 2022)Publisher Copyright: © 2022 Royal Society Publishing. All rights reserved..
vor 2 Monaten von @scadsfct
alle anzeigen
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)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1RTASS: a RunTime Adaptable and Scalable System for Network-on-Chip-Based Architectures
N. Charaf, J. Haase, A. Kulisch, {. Elm, und D. Göhringer. 2023 26th Euromicro Conference on Digital System Design (DSD), Seite 585--592. IEEE, (08.09.2023)Publisher Copyright: © 2023 IEEE.; 26th Euromicro Conference on Digital System Design, DSD 2023 ; Conference date: 06-09-2023 Through 08-09-2023.
vor 2 Monaten von @scadsfct
alle anzeigen
topic_federatedlearn
Computer
Embedded
FIS_scads
Machine
Runtime,
Scalability,
Shape
algorithms,
architecture,
computing,
learning
vision,
topic_federatedlearnComputerEmbeddedFIS_scadsMachineRuntime,Scalability,Shapealgorithms,architecture,computing,learningvision,
(0)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1Data-driven determination of plant growth stages for improved weather index insurance design
J. Zou, M. Odening, und O. Okhrin. Agricultural Finance Review, (2024)Publisher Copyright: © 2024, Jing Zou, Martin Odening and Ostap Okhrin..
vor 2 Monaten von @scadsfct
alle anzeigen
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)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1Identifying Secondary School Students' Misconceptions about Machine Learning: An Interview Study
E. Marx, C. Witt, und T. Leonhardt. WiPSCE '24: Proceedings of the 19th WiPSCE Conference on Primary and Secondary Computing Education Research, Seite 1--10. Association for Computing Machinery, (16.09.2024)Publisher Copyright: © 2024 Copyright held by the owner/author(s)..
vor 2 Monaten von @scadsfct
alle anzeigen
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)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1Brief Summary of Existing Research on Students’ Conceptions of AI
E. Marx, T. Leonhardt, und N. Bergner. (Oktober 2022)Publisher Copyright: © 2022 Owner/Author.; WiPSCE 2022 ; Conference date: 31-10-2022 Through 02-11-2022.
vor 2 Monaten von @scadsfct
alle anzeigen
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)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
2Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning
L. Lange, M. Heykeroth, und E. Rahm. arXiv preprint arXiv:2409.01329, (September 2024)
vor 2 Monaten von @scadsfct
alle anzeigen
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)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1Chapter 5 - Artificial intelligence (AI) enhanced nanomotors and active matter
F. Cichos, S. Landin, und R. Pradip. Intelligent Nanotechnology, Elsevier, (2023)
vor 4 Monaten von @scadsfct
alle anzeigen
topic_physchemistry
Active
Feedback
Machine
Multi
Optical
Reinforcement
agent
control
control,
learning,
particles,
reinforcement
topic_physchemistryActiveFeedbackMachineMultiOpticalReinforcementagentcontrolcontrol,learning,particles,reinforcement
(0)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1Stability selection enables robust learning of partial differential equations from limited noisy data
S. Maddu, B. Cheeseman, I. Sbalzarini, und C. Müller. (2019)
vor 4 Monaten von @scadsfct
alle anzeigen
(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)
KopierenLöschenDiese Publikation zur Ablage hinzufügen
1NDP-RANK: Prediction and ranking of NDP systems performance using machine learning
V. Iskandar, M. Abd El Ghany, und D. Goehringer. Microprocessors and Microsystems, (2023)
vor 4 Monaten von @scadsfct
alle anzeigen
topic_federatedlearn
Design
Machine
Modeling,
Near-data
Prediction,
exploration
learning,
processing,
space
topic_federatedlearnDesignMachineModeling,Near-dataPrediction,explorationlearning,processing,space
(0)
KopierenLöschenDiese Publikation zur Ablage hinzufügen

⟨⟨
⟨
1
2
⟩
⟩⟩

PUMA

Lesezeichen (verstecken)
Anzeige
alles
nur Lesezeichen
Lesezeichen pro Seite
5
10
20
50
100
sortieren nach
hinzugefügt am
Titel
RSS
BibTeX
XML

Publikationen (verstecken)33
Anzeige
alles
nur Publikationen
Publikationen pro Seite
5
10
20
50
100
sortieren nach
hinzugefügt am
Titel
Autor
Erscheinungsdatum
Eintragstyp
Hilfe für erweiterte Sortierung...
RSS
BibTeX
RDF
mehr...

1MLcps: machine learning cumulative performance score for classification problems

1Cost-Sensitive Best Subset Selection for Logistic Regression: A Mixed-Integer Conic Optimization Perspective

1Extendable hybrid approach to detect conscious states in a CLIS patient using machine learning

2Evaluating the DoC-Forest tool for Classifying the State of Consciousness in a Completely Locked-In Syndrome Patient

1Machine Learning Based Mobile Capacity Estimation for Roadside Parking

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

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

1Chapter 5 - Artificial intelligence (AI) enhanced nanomotors and active matter

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

1NDP-RANK: Prediction and ranking of NDP systems performance using machine learning

Stöbern

Verwandte Tags

Konzepte

Tags

Lesezeichen (verstecken) Anzeigeallesnur LesezeichenLesezeichen pro Seite5102050100 sortieren nachhinzugefügt amTitel RSSBibTeXXML

Publikationen (verstecken)33 Anzeigeallesnur PublikationenPublikationen pro Seite5102050100 sortieren nachhinzugefügt amTitelAutorErscheinungsdatumEintragstypHilfe für erweiterte Sortierung... RSSBibTeXRDFmehr...

Stöbern

Verwandte Tags

Tags

Lesezeichen (verstecken)
Anzeige
alles
nur Lesezeichen
Lesezeichen pro Seite
5
10
20
50
100
sortieren nach
hinzugefügt am
Titel
RSS
BibTeX
XML

Publikationen (verstecken)33
Anzeige
alles
nur Publikationen
Publikationen pro Seite
5
10
20
50
100
sortieren nach
hinzugefügt am
Titel
Autor
Erscheinungsdatum
Eintragstyp
Hilfe für erweiterte Sortierung...
RSS
BibTeX
RDF
mehr...