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Viewing Publication 1 - 23 from 23

2013

Artificial Intelligence Applications in BiomedicinePanayiotis Vlamos, Konstantinos Lefkimmiatis, Catalina Cocianu, Luminita State, Zhiyuan Luo. advai, 2013, 2013. [doi]

2012

Heuristic Attempts to Improve the Generalization Capacities in Learning SVMsLuminita State, Catalina Cocianu, Marinela Mircea. snpd 2012: 108-113 [doi]

2011

A New Method for Learning the Support Vector MachinesCatalina-Lucia Cocianu, Luminita State, Panayiotis Vlamos. ICSOFT 2011: 365-370

A Probabilistic Model-Free Approach in Learning Multivariate Noisy Linear SystemsLuminita State, Iuliana Paraschiv-Munteanu. synasc 2011: 239-246 [doi]

A New Linear Classifier Based on Combining Supervised and Unsupervised TechniquesLuminita State, Iuliana Paraschiv-Munteanu. ijccc, 6(1):175-186, 2011. [doi]

2009

PCA Supervised and Unsupervised Classifiers in Signal ProcessingCatalina Cocianu, Luminita State, Panayiotis Vlamos, Doru Constantin, Corina Sararu. pris 2009: 61-70

Toward a Semi-supervised Approach in Classification based on Principal DirectionsLuminita State, Catalina Cocianu, Doru Constantin, Corina Sararu, Panayiotis Vlamos. sigmap 2009: 68-73

2008

Decorrelation Techniques in Image RestorationCatalina Cocianu, Luminita State, Panayiotis Vlamos, Doru Constantin. sigmap 2008: 193-196

The FastICA Algorithm Based on Successive Approximations with Superior Convergence RateDoru Constantin, Luminita State. iih-msp 2008: 909-912 [doi]

A Version of the FastICA Algorithm Based on the Secant Method Combined with Simple Iterations MethodDoru Constantin, Luminita State. icisp 2008: 312-320 [doi]

An Improved Algorithm for Estimating the ICA Model Concerning the Convergence RateDoru Constantin, Luminita State. amdo 2008: 400-408 [doi]

A New Learning Algorithm for Classification in the Reduced SpaceLuminita State, Catalina Cocianu, Ion Rosca, Panayiotis Vlamos. ICEIS 2007: 155-160

An unsupervised skeleton based method to discover the structure of the class systemLuminita State, Catalina Cocianu, Panayiotis Vlamos. rcis 2008: 169-178 [doi]

Neural Approaches to Image Compression/Decompression Using PCA based Learning AlgorithmsLuminita State, Catalina Cocianu, Panayiotis Vlamos, Doru Constantin. pris 2008: 187-192

2007

A New Adaptive Classification Scheme Based on Skeleton InformationCatalina Cocianu, Luminita State, Ion Rosca, Panayiotis Vlamos. sigmap 2007: 85-92

A Connectionist Approach in Bayesian ClassificationLuminita State, Catalina Cocianu, Panayiotis Vlamos, Viorica Stefanescu. ICEIS 2007: 185-190

Principal Directions-Based Algorithm for Classification TasksLuminita State, Catalina Cocianu, Panayiotis Vlamos, Doru Constantin. synasc 2007: 137-143 [doi]

2006

PCA-based data mining probabilistic and fuzzy approaches with applications in pattern recognitionLuminita State, Catalina Cocianu, Panayiotis Vlamos, Viorica Stefanescu. ICSOFT 2006: 55-60

2004

On the Efficiency of a Certain Class of Noise Removal Algorithms in Solving Image Processing TasksCatalina Cocianu, Luminita State, Panayiotis Vlamos, Viorica Stefanescu. icinco 2004: 320-323

A Neural Network Framework for Implementing the Bayesian LearningLuminita State, Catalina Cocianu, Viorica Stefanescu, Panayiotis Vlamos. icinco 2004: 328-331

2002

On a Certain Class of Algorithms for Noise Removal in Image Processing: A Comparative StudyCatalina Cocianu, Luminita State, Panayiotis Vlamos. itcc 2002: 111-116 [doi]

1996

Evolutionary/genetic programming in restricted domainsLuminita State, Stuart Rubin, Radu State. npsc, 4(4):419-444, 1996. [doi]

1995

And/Or Trees for Knowledge RepresentationLuminita State, Radu State. ecsqaru 1995: 405-411

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