scadsfct > Machine

bookmarks (hide)
display
all
bookmarks only
bookmarks per page
5
10
20
50
100
sort by
added at
title
RSS
BibTeX
XML

No matching posts.

⟨⟨
⟨
⟩
⟩⟩

publications (hide)29
display
all
publications only
publications per page
5
10
20
50
100
sort by
added at
title
author
publication date
entry type
help for advanced sorting...
RSS
BibTeX
RDF
more...

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..
20 days ago by @scadsfct
show all tags
FIS_scads
Generalized
insurance
additive
model,
index
risk,
basis
Machine
stages,
Plant
learning,
Weather
Temporal
growth
topic_engineering
FIS_scadsGeneralizedinsuranceadditivemodel,indexrisk,basisMachinestages,Plantlearning,WeatherTemporalgrowthtopic_engineering
copydeleteadd this publication to your clipboard
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..
20 days ago by @scadsfct
show all tags
Animals,
FIS_scads
Infarction,
Macrophages,
Cardiac/metabolism,
Macrophages/metabolism,
Mice,
Myocytes,
C57BL,
Machine
learning,
Myocardial
topic_lifescience
Immunocompromised,
Single-cell,
infarction,
therapy,
Inbred
Cell
Monocytes/metabolism
Animals,FIS_scadsInfarction,Macrophages,Cardiac/metabolism,Macrophages/metabolism,Mice,Myocytes,C57BL,Machinelearning,Myocardialtopic_lifescienceImmunocompromised,Single-cell,infarction,therapy,InbredCellMonocytes/metabolism
copydeleteadd this publication to your clipboard
1Impact of pre- and post-processing steps for supervised classification of colorectal cancer in hyperspectral images
M. Tkachenko, C. Chalopin, B. Jansen-Winkeln, T. Neumuth, I. Gockel, and M. Maktabi. Cancers (Basel), (April 2023)
3 months ago by @scadsfct
show all tags
convolutional
learning;
cancer
networks;
imaging;
classification;
pre-processing
post-processing;
cancer;
filter;
colorectal
median
machine
hyperspectral
topic_lifescience
convolutionallearning;cancernetworks;imaging;classification;pre-processingpost-processing;cancer;filter;colorectalmedianmachinehyperspectraltopic_lifescience
copydeleteadd this publication to your clipboard
1Structural damage identification of composite rotors based on fully connected neural networks and convolutional neural networks
V. Scholz, P. Winkler, A. Hornig, M. Gude, and A. Filippatos. Sensors (Basel), 21 (6): 2005 (March 2021)
3 months ago by @scadsfct
show all tags
convolutional
(SHM)
monitoring
learning;
neural
networks;
rotors;
health
dense
composites;
connected
structural
composite
machine
fully
convolutional(SHM)monitoringlearning;neuralnetworks;rotors;healthdensecomposites;connectedstructuralcompositemachinefully
copydeleteadd this publication to your clipboard
1Explaining the Unexplainable: The Impact of Misleading Explanations on Trust in Unreliable Predictions for Hardly Assessable Tasks
M. Sadeghi, D. Pöttgen, P. Ebel, and A. Vogelsang. Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization, page 36–46. New York, NY, USA, Association for Computing Machinery, (2024)
3 months ago by @scadsfct
show all tags
XAI,
learning,
explainability,
machine
topic_visualcomputing
trust
XAI,learning,explainability,machinetopic_visualcomputingtrust
copydeleteadd this publication to your clipboard
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)
8 days ago by @scadsfct
show all tags
rates
forecasting
machine
autoconversion
learning
satellite
ratesforecastingmachineautoconversionlearningsatellite
copydeleteadd this publication to your clipboard
1Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction
D. Nam, J. Chapiro, V. Paradis, T. Seraphin, and J. Kather. JHEP Rep., 4 (4): 100443 (April 2022)
3 months ago by @scadsfct
show all tags
a
disease;
HCC,
or
intelligence;
liver
multivariable
non-alcoholic
multimodal
ML,
artificial
WSIs,
images;
prediction
support
integration
TACE,
DICOM,
AI,
network;
deep
neural
Digital
Diagnosis;
MVI,
transarterial
fatty
topic_lifescience
microvascular
convolutional
in
learning;
imaging;
Communications
invasion;
NAFLD,
chemoembolisation;
hepatocellular
Reporting
steatohepatitis;
Transparent
Individual
slide
machine
Prognosis
Artificial
data
for
NASH,
whole
Medicine;
TRIPOD,
of
CNN,
and
Imaging
carcinoma;
diagnostic
system;
model
adisease;HCC,orintelligence;livermultivariablenon-alcoholicmultimodalML,artificialWSIs,images;predictionsupportintegrationTACE,DICOM,AI,network;deepneuralDigitalDiagnosis;MVI,transarterialfattytopic_lifesciencemicrovascularconvolutionalinlearning;imaging;Communicationsinvasion;NAFLD,chemoembolisation;hepatocellularReportingsteatohepatitis;TransparentIndividualslidemachinePrognosisArtificialdataforNASH,wholeMedicine;TRIPOD,ofCNN,andImagingcarcinoma;diagnosticsystem;model
copydeleteadd this publication to your clipboard
1Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network
S. Mukherjee, J. Cogan, J. Newman, J. Phillips, 3rd, R. Hamid, Undiagnosed Diseases Network, J. Meiler, and J. Capra. Am. J. Hum. Genet., 108 (10): 1946--1963 (October 2021)
3 months ago by @scadsfct
show all tags
disease;
prediction;
disease
learning;
Network;
oligogenic
Diseases
clinical
digenic
rare
machine
topic_lifescience
Undiagnosed
UDN;
disease;prediction;diseaselearning;Network;oligogenicDiseasesclinicaldigenicraremachinetopic_lifescienceUndiagnosedUDN;
copydeleteadd this publication to your clipboard
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)..
20 days ago by @scadsfct
show all tags
FIS_scads
models,
students
mental
misconceptions,
artificial
research,
intelligence,
qualitative
study,
learning,
machine
interview
area_responsibleai
conceptions
FIS_scadsmodels,studentsmentalmisconceptions,artificialresearch,intelligence,qualitativestudy,learning,machineinterviewarea_responsibleaiconceptions
copydeleteadd this publication to your clipboard
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.
20 days ago by @scadsfct
show all tags
FIS_scads
models,
education,
mental
preconceptions
artificial
ideas,
beliefs,
intelligence,
k-12
learning,
machine
conceptions,
area_responsibleai
FIS_scadsmodels,education,mentalpreconceptionsartificialideas,beliefs,intelligence,k-12learning,machineconceptions,area_responsibleai
copydeleteadd this publication to your clipboard
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
(physics.data-an),
Analysis,
Probability
Data
sciences,
Numerical
Statistics
FOS:
Machine
Physical
sciences
Analysis
(cs.LG),
Learning
(math.NA),
Mathematics,
and
Computer
information
(physics.data-an),Analysis,ProbabilityDatasciences,NumericalStatisticsFOS:MachinePhysicalsciencesAnalysis(cs.LG),Learning(math.NA),Mathematics,andComputerinformation
copydeleteadd this publication to your clipboard
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..
20 days ago by @scadsfct
show all tags
FIS_scads
PAR
statistical
proteins,
equations,
learning
selection,
sparse
differential
regression,
learning,
machine
topic_lifescience
stability
theory
FIS_scadsPARstatisticalproteins,equations,learningselection,sparsedifferentialregression,learning,machinetopic_lifesciencestabilitytheory
copydeleteadd this publication to your clipboard
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)
20 days ago by @scadsfct
show all tags
ep
FOS:
Machine
sciences
(cs.LG),
Security
Learning
(cs.CV),
and
Vision
Computer
(cs.CR),
Cryptography
information
Pattern
area_bigdata
area_responsibleai
Recognition
epFOS:Machinesciences(cs.LG),SecurityLearning(cs.CV),andVisionComputer(cs.CR),CryptographyinformationPatternarea_bigdataarea_responsibleaiRecognition
copydeleteadd this publication to your clipboard
1Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging
L. Lampe, H. Huppertz, S. Anderl-Straub, F. Albrecht, T. Ballarini, S. Bisenius, K. Mueller, S. Niehaus, K. Fassbender, K. Fliessbach and 13 other author(s). NeuroImage Clin., 37 (103320): 103320 (January 2023)
3 months ago by @scadsfct
show all tags
MRI;
Neurodegeneration;
learning;
unit_test
Diagnosis;
Volumetry
topic_lifescience
topic_neuroinspired
Dementia;
Machine
MRI;Neurodegeneration;learning;unit_testDiagnosis;Volumetrytopic_lifesciencetopic_neuroinspiredDementia;Machine
copydeleteadd this publication to your clipboard
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)
8 days ago by @scadsfct
show all tags
Learning
Capacity
Parking
Estimation
Roadside
Based
Mobile
Machine
LearningCapacityParkingEstimationRoadsideBasedMobileMachine
copydeleteadd this publication to your clipboard
1Common features in lncRNA annotation and classification: A survey
C. Klapproth, R. Sen, P. Stadler, S. Findeiß, and J. Fallmann. Noncoding RNA, 7 (4): 77 (December 2021)
3 months ago by @scadsfct
show all tags
problems;
coding
extraction;
feature
sequence;
machine
lncRNA;
learning
classification
problems;codingextraction;featuresequence;machinelncRNA;learningclassification
copydeleteadd this publication to your clipboard
1Automated algorithm selection on continuous black-box problems by combining Exploratory Landscape Analysis and machine learning
P. Kerschke, and H. Trautmann. Evol. Comput., 27 (1): 99--127 (2019)
3 months ago by @scadsfct
show all tags
learning;
single-objective
analysis;
black-box
exploratory
optimization;
continuous
machine
optimization.
Automated
selection;
algorithm
landscape
learning;single-objectiveanalysis;black-boxexploratoryoptimization;continuousmachineoptimization.Automatedselection;algorithmlandscape
copydeleteadd this publication to your clipboard
1Automated algorithm selection: Survey and perspectives
P. Kerschke, H. Hoos, F. Neumann, and H. Trautmann. Evol. Comput., 27 (1): 3--45 (2019)
3 months ago by @scadsfct
show all tags
feature-based
learning;
metalearning
data
analysis;
optimisation;
automated
streams.;
exploratory
combinatorial
continuous
machine
approaches;
Automated
selection;
algorithm
configuration;
landscape
feature-basedlearning;metalearningdataanalysis;optimisation;automatedstreams.;exploratorycombinatorialcontinuousmachineapproaches;Automatedselection;algorithmconfiguration;landscape
copydeleteadd this publication to your clipboard
1NDP-RANK: Prediction and ranking of NDP systems performance using machine learning
V. Iskandar, M. Abd El Ghany, and D. Goehringer. Microprocessors and Microsystems, (2023)
3 months ago by @scadsfct
show all tags
Near-data
Modeling,
topic_federatedlearn
exploration
Design
processing,
learning,
space
Machine
Prediction,
Near-dataModeling,topic_federatedlearnexplorationDesignprocessing,learning,spaceMachinePrediction,
copydeleteadd this publication to your clipboard
1Stroke-GFCN: ischemic stroke lesion prediction with a fully convolutional graph network
A. Iporre-Rivas, D. Saur, K. Rohr, G. Scheuermann, and C. Gillmann. J. Med. Imaging (Bellingham), 10 (4): 044502 (July 2023)
3 months ago by @scadsfct
show all tags
stroke
medical
learning;
neural
networks;
imaging;
machine
prediction
multi-modal
topic_visualcomputing
graph
strokemedicallearning;neuralnetworks;imaging;machinepredictionmulti-modaltopic_visualcomputinggraph
copydeleteadd this publication to your clipboard
1Proteomic profiling of low muscle and high fat mass: a machine learning approach in the KORA S4/FF4 study
M. Huemer, A. Bauer, A. Petrera, M. Scholz, S. Hauck, M. Drey, A. Peters, and B. Thorand. J. Cachexia Sarcopenia Muscle, 12 (4): 1011--1023 (August 2021)
3 months ago by @scadsfct
show all tags
mass
index;
skeletal
learning;
Appendicular
mass;
Machine
Proteomics
muscle
Fat
fat
Muscle
Body
massindex;skeletallearning;Appendicularmass;MachineProteomicsmuscleFatfatMuscleBody
copydeleteadd this publication to your clipboard
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..
20 days ago by @scadsfct
show all tags
FIS_scads
Learning,
Health
Diseases/therapy,
Germany,
Interoperability/standards,
Information
Electronic
Machine
Humans,
Eye
Records/standards,
topic_lifescience
Ophthalmology
Seven/standards,
Level
FIS_scadsLearning,HealthDiseases/therapy,Germany,Interoperability/standards,InformationElectronicMachineHumans,EyeRecords/standards,topic_lifescienceOphthalmologySeven/standards,Level
copydeleteadd this publication to your clipboard
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).
20 days ago by @scadsfct
show all tags
FIS_scads
Fiber
modeling,
area_architectures
plastics,
reinforced
Constitutive
Machine
identification
learning,
networks,
Parameter
topic_engineering
Neural
FIS_scadsFibermodeling,area_architecturesplastics,reinforcedConstitutiveMachineidentificationlearning,networks,Parametertopic_engineeringNeural
copydeleteadd this publication to your clipboard
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.
20 days ago by @scadsfct
show all tags
Convolutional
FIS_scads
Fiber
area_architectures
neural
plastics
rate
dependency,
reinforced
Direct
Strain
Machine
learning,
networks,
identification,
parameter
topic_engineering
ConvolutionalFIS_scadsFiberarea_architecturesneuralplasticsratedependency,reinforcedDirectStrainMachinelearning,networks,identification,parametertopic_engineering
copydeleteadd this publication to your clipboard
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
agent
particles,
Optical
Multi
control
Machine
Active
Feedback
learning,
Reinforcement
topic_physchemistry
reinforcement
control,
agentparticles,OpticalMulticontrolMachineActiveFeedbacklearning,Reinforcementtopic_physchemistryreinforcementcontrol,
copydeleteadd this publication to your clipboard
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.
20 days ago by @scadsfct
show all tags
FIS_scads
Shape
learning
Machine
computing,
topic_federatedlearn
Runtime,
vision,
algorithms,
architecture,
Embedded
Computer
Scalability,
FIS_scadsShapelearningMachinecomputing,topic_federatedlearnRuntime,vision,algorithms,architecture,EmbeddedComputerScalability,
copydeleteadd this publication to your clipboard
1Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis
A. Akshay, M. Katoch, N. Shekarchizadeh, M. Abedi, A. Sharma, F. Burkhard, R. Adam, K. Monastyrskaya, and A. Gheinani. Gigascience, (January 2024)
3 months ago by @scadsfct
show all tags
problems;
topic_federatedlearn
visualization
learning;
data
machine
analysis;
AutoML;
classification
problems;topic_federatedlearnvisualizationlearning;datamachineanalysis;AutoML;classification
copydeleteadd this publication to your clipboard
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, and A. Gheinani. Gigascience, (December 2022)
3 months ago by @scadsfct
show all tags
problems;
topic_federatedlearn
score
unified
learning;
package;
evaluation
machine
Python
evaluation;
model
classification
problems;topic_federatedlearnscoreunifiedlearning;package;evaluationmachinePythonevaluation;modelclassification
copydeleteadd this publication to your clipboard
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)
20 days ago by @scadsfct
show all tags
FIS_scads
Humans,
Factual,
Learning,
Health
topic_lifescience
Medical
Electronic
Informatics,
Records
Databases,
Machine
FIS_scadsHumans,Factual,Learning,Healthtopic_lifescienceMedicalElectronicInformatics,RecordsDatabases,Machine
copydeleteadd this publication to your clipboard

⟨⟨
⟨
1
⟩
⟩⟩

PUMA

bookmarks (hide)
display
all
bookmarks only
bookmarks per page
5
10
20
50
100
sort by
added at
title
RSS
BibTeX
XML

publications (hide)29
display
all
publications only
publications per page
5
10
20
50
100
sort by
added at
title
author
publication date
entry type
help for advanced sorting...
RSS
BibTeX
RDF
more...

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

1CCR2 macrophage response determines the functional outcome following cardiomyocyte transplantation

1Impact of pre- and post-processing steps for supervised classification of colorectal cancer in hyperspectral images

1Structural damage identification of composite rotors based on fully connected neural networks and convolutional neural networks

1Explaining the Unexplainable: The Impact of Misleading Explanations on Trust in Unreliable Predictions for Hardly Assessable Tasks

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

1Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction

1Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network

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

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

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

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

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

1Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging

1Machine Learning Based Mobile Capacity Estimation for Roadside Parking

1Common features in lncRNA annotation and classification: A survey

1Automated algorithm selection on continuous black-box problems by combining Exploratory Landscape Analysis and machine learning

1Automated algorithm selection: Survey and perspectives

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

1Stroke-GFCN: ischemic stroke lesion prediction with a fully convolutional graph network

1Proteomic profiling of low muscle and high fat mass: a machine learning approach in the KORA S4/FF4 study

1Towards Standardizing Ophthalmic Data for Seamless Interoperability in Eye Care

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

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

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

1Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis

1MLcps: machine learning cumulative performance score for classification problems

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

browse

related tags

concepts

tags

bookmarks (hide) displayallbookmarks onlybookmarks per page5102050100 sort byadded attitle RSSBibTeXXML

publications (hide)29 displayallpublications onlypublications per page5102050100 sort byadded attitleauthorpublication dateentry typehelp for advanced sorting... RSSBibTeXRDFmore...

browse

related tags

tags

bookmarks (hide)
display
all
bookmarks only
bookmarks per page
5
10
20
50
100
sort by
added at
title
RSS
BibTeX
XML

publications (hide)29
display
all
publications only
publications per page
5
10
20
50
100
sort by
added at
title
author
publication date
entry type
help for advanced sorting...
RSS
BibTeX
RDF
more...