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publications (hide)18
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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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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 @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)
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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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1Efficient Raycasting of View-Dependent Piecewise Constant Representations of Volumetric Data
A. Gupta, U. Günther, P. Incardona, G. Reina, S. Frey, S. Gumhold, and {. Sbalzarini. WorkingPaper, (Jun 17, 2022)
13 days ago by @scadsfct
show all tags
topic_visualcomputing
topic_lifescience
FIS_scads
Human-centered
Visualization
Visualization,
and
computing,
concepts
paradigms,
techniques
theory,
topic_visualcomputingtopic_lifescienceFIS_scadsHuman-centeredVisualizationVisualization,andcomputing,conceptsparadigms,techniquestheory,
(0)
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1Content-adaptive generation and parallel compositing of volumetric depth images for responsive visualization of large volume data
A. Gupta, P. Incardona, P. Hunt, G. Reina, S. Frey, S. Gumhold, U. Günther, and {. Sbalzarini. WorkingPaper, (Jun 29, 2022)
13 days ago by @scadsfct
show all tags
topic_visualcomputing
topic_lifescience
FIS_scads
Human-centered
Visualization
Visualization,
and
computing,
concepts
paradigms
techniques
theory,
topic_visualcomputingtopic_lifescienceFIS_scadsHuman-centeredVisualizationVisualization,andcomputing,conceptsparadigmstechniquestheory,
(0)
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1The Rad52 SSAP superfamily and new insight into homologous recombination
A. Al-Fatlawi, M. Schroeder, and {. Stewart. Communications biology, (Jan 23, 2023)Funding Information: We gratefully acknowledge support from ZIH of TU Dresden and the BMBF Project scads.ai..
13 days ago by @scadsfct
show all tags
topic_lifescience
DNA
FIS_scads
Homologous
Protein/genetics
Rad52
Recombination
Recombination,
Repair
and
topic_lifescienceDNAFIS_scadsHomologousProtein/geneticsRad52RecombinationRecombination,Repairand
(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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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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1Personalized structural biology reveals the molecular mechanisms underlying heterogeneous epileptic phenotypes caused by de novo KCNC2 variants
S. Mukherjee, T. Cassini, N. Hu, T. Yang, B. Li, W. Shen, C. Moth, D. Rinker, J. Sheehan, J. Cogan and 8 other author(s). Human Genetics and Genomics Advances, 3 (4): 100131 (2022)
2 months ago by @scadsfct
show all tags
topic_lifescience
DEE,
Diseases
KCNC2,
Network,
Undiagnosed
and
biology,
developmental
disease
dynamics
electrophysiology,
encephalopathy,
epileptic
interpretation,
molecular
personalized
rare
simulations,
structural
variant
variant,
topic_lifescienceDEE,DiseasesKCNC2,Network,Undiagnosedandbiology,developmentaldiseasedynamicselectrophysiology,encephalopathy,epilepticinterpretation,molecularpersonalizedraresimulations,structuralvariantvariant,
(0)
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1If there's a Trigger Warning, then where's the Trigger? Investigating Trigger Warnings at the Passage Level
M. Wiegmann, J. Rakete, M. Wolska, B. Stein, and M. Potthast. (2024)
2 months ago by @scadsfct
show all tags
topic_language
(cs.CL),
(cs.CY),
Computation
Computer
Computers
FOS:
Language
Society
and
information
sciences
sciences,
topic_language(cs.CL),(cs.CY),ComputationComputerComputersFOS:LanguageSocietyandinformationsciencessciences,
(0)
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1Graph Mining for Complex Data Analytics
A. Petermann, M. Junghanns, S. Kemper, K. Gómez, N. Teichmann, and E. Rahm. 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), page 1316--1319. (December 2016)
2 months ago by @scadsfct
show all tags
Data
Intelligence
Mining;Business
algorithms;Conferences;Graph
analysis;Data
and
design
mining;Business;Algorithm
models;Libraries;Partitioning
DataIntelligenceMining;Businessalgorithms;Conferences;Graphanalysis;Dataanddesignmining;Business;Algorithmmodels;Libraries;Partitioning
(0)
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1Modeling Proficiency with Implicit User Representations
K. Breitwieser, A. Lahnala, C. Welch, L. Flek, and M. Potthast. (2021)
2 months ago by @scadsfct
show all tags
(cs.CL),
Computation
Computer
FOS:
Language
and
information
sciences
sciences,
(cs.CL),ComputationComputerFOS:Languageandinformationsciencessciences,
(0)
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1Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer
S. Brockmoeller, A. Echle, N. Ghaffari Laleh, S. Eiholm, M. Malmstrøm, T. Plato Kuhlmann, K. Levic, H. Grabsch, N. West, O. Saldanha and 7 other author(s). J. Pathol., 256 (3): 269--281 (March 2022)
3 months ago by @scadsfct
show all tags
topic_lifescience
AI;
LNM
adipose
and
artificial
biomarker;
bowel
cancer;
colorectal
deep
digital
early
inflamed
intelligence;
learning;
metastasis;
new
pT1
pT2
pathology;
prediction
predictive
tissue;
topic_lifescienceAI;LNMadiposeandartificialbiomarker;bowelcancer;colorectaldeepdigitalearlyinflamedintelligence;learning;metastasis;newpT1pT2pathology;predictionpredictivetissue;
(0)
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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
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
topic_lifescienceAI,ArtificialCNN,CommunicationsDICOM,Diagnosis;DigitalHCC,ImagingIndividualML,MVI,Medicine;NAFLD,NASH,PrognosisReportingTACE,TRIPOD,TransparentWSIs,aandartificialcarcinoma;chemoembolisation;convolutionaldatadeepdiagnosticdisease;fattyforhepatocellularimages;imaging;inintegrationintelligence;invasion;learning;livermachinemicrovascularmodelmultimodalmultivariablenetwork;neuralnon-alcoholicoforpredictionslidesteatohepatitis;supportsystem;transarterialwhole
(0)
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1Classification of hyperspectral endocrine tissue images using support vector machines
M. Maktabi, H. Köhler, M. Ivanova, T. Neumuth, N. Rayes, L. Seidemann, R. Sucher, B. Jansen-Winkeln, I. Gockel, M. Barberio and 1 other author(s). Int. J. Med. Robot., 16 (5): 1--10 (October 2020)
3 months ago by @scadsfct
show all tags
and
assisted
computer
guided
head
imaged
imaging;
intraoperative
neck;
surgery;
thyroidectomy
andassistedcomputerguidedheadimagedimaging;intraoperativeneck;surgery;thyroidectomy
(0)
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1Modeling and processing up-to-dateness of patient information in probabilistic therapy decision support
J. Gaebel, H. Wu, A. Oeser, M. Cypko, M. Stoehr, A. Dietz, T. Neumuth, S. Franke, and S. Oeltze-Jafra. Artif. Intell. Med., 104 (101842): 101842 (April 2020)
3 months ago by @scadsfct
show all tags
Arden
Decision
Head
Medical
Therapy
and
decision
delay;
logic
model
modules;
neck
oncology;
support
syntax;
system;
ArdenDecisionHeadMedicalTherapyanddecisiondelay;logicmodelmodules;neckoncology;supportsyntax;system;
(0)
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