2023 - Research.com Computer Science in Denmark Leader Award
2022 - Research.com Computer Science in Denmark Leader Award
Lars Kai Hansen mainly focuses on Artificial intelligence, Pattern recognition, Machine learning, Artificial neural network and Independent component analysis. His study in Pattern recognition is interdisciplinary in nature, drawing from both Voxel, Data mining, Brain mapping and Test set. His Machine learning study combines topics from a wide range of disciplines, such as Superposition principle, Multilinear principal component analysis, Invariant and Convex hull.
His work carried out in the field of Artificial neural network brings together such families of science as Tensor, Current and Pattern recognition. His Independent component analysis research is multidisciplinary, incorporating perspectives in Electroencephalography, Toolbox, Speech recognition, Functional magnetic resonance imaging and Algorithm. His studies deal with areas such as Fault tolerance, Regularization and Cross-validation as well as Generalization error.
His main research concerns Artificial intelligence, Pattern recognition, Machine learning, Artificial neural network and Algorithm. His research integrates issues of Natural language processing, Computer vision and Electroencephalography in his study of Artificial intelligence. He has included themes like Speech recognition, Neuroimaging and Cluster analysis in his Pattern recognition study.
His studies in Artificial neural network integrate themes in fields like Generalization and Pruning. His research on Algorithm frequently connects to adjacent areas such as Blind signal separation.
Lars Kai Hansen mostly deals with Artificial intelligence, Electroencephalography, Pattern recognition, Machine learning and Artificial neural network. His study looks at the relationship between Artificial intelligence and fields such as Functional magnetic resonance imaging, as well as how they intersect with chemical problems. His Electroencephalography study integrates concerns from other disciplines, such as Stimulus, Attentional modulation, Speech recognition and Neuroimaging.
His study on Pattern recognition also encompasses disciplines like
Lars Kai Hansen spends much of his time researching Electroencephalography, Artificial intelligence, Pattern recognition, Algorithm and Sleep Stages. The various areas that Lars Kai Hansen examines in his Electroencephalography study include Machine learning, Neuroimaging, Temporal resolution and Human–computer interaction. His Machine learning research incorporates elements of Cerebral cortex, Data-driven and Image resolution.
His study brings together the fields of Data acquisition and Artificial intelligence. In his study, Computational complexity theory, Inference, Covariance and Brain mapping is strongly linked to Inverse problem, which falls under the umbrella field of Pattern recognition. His Algorithm research is multidisciplinary, incorporating elements of Probability distribution, Latent variable, Cluster analysis, Curvature and Gibbs sampling.
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Neural network ensembles
L.K. Hansen;P. Salamon.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1990)
Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner’s Handbook
Magnus Nrgaard;O. E. Ravn;N. K. Poulsen;L. K. Hansen.
Neural Networks for Modelling and Control of Dynamic Systems
M. Nørgaard;O. Ravn;N. K. Poulsen;L. K. Hansen.
On Clustering fMRI Time Series
Cyril Goutte;Peter Aundal Toft;Egill Rostrup;Finn Årup Nielsen.
Independent component analysis of functional MRI: what is signal and what is noise?
Martin J McKeown;Lars Kai Hansen;Terrence J Sejnowsk;Terrence J Sejnowsk.
Current Opinion in Neurobiology (2003)
Good Friends, Bad News - Affect and Virality in Twitter
Lars Kai Hansen;Adam Arvidsson;Finn Aarup Nielsen;Elanor Colleoni.
international conference on future information technology (2011)
Melanoma Diagnosis by Raman Spectroscopy and Neural Networks: Structure Alterations in Proteins and Lipids in Intact Cancer Tissue
Monika Gniadecka;Peter Alshede Philipsen;Sigurdur Sigurdsson;Sonja Wessel.
Journal of Investigative Dermatology (2004)
Circulating Levels of MicroRNA from Children with Newly Diagnosed Type 1 Diabetes and Healthy Controls: Evidence That miR-25 Associates to Residual Beta-Cell Function and Glycaemic Control during Disease Progression
Lotte B. Nielsen;Cheng Wang;Kaspar Sorensen;Claus Heiner Bang-Berthelsen.
Experimental Diabetes Research (2012)
Detection of skin cancer by classification of Raman spectra
S. Sigurdsson;P.A. Philipsen;L.K. Hansen;J. Larsen.
IEEE Transactions on Biomedical Engineering (2004)
The quantitative evaluation of functional neuroimaging experiments: The NPAIRS data analysis framework
Stephen C. Strother;Jon R. Anderson;Jon R. Anderson;Lars Kai Hansen;Ulrik Kjems.
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