- Inverse Free Universum Twin Support Vector Machine2021 | Matematicko-fyzikální fakulta
- Inverse free reduced universum twin support vector machine for imbalanced data classification2023 | Matematicko-fyzikální fakulta
- Flood Simulations Using a Sensor Network and Support Vector Machine Model2023 | Přírodovědecká fakulta
- Non-Asymptotic Analysis of l(1)-Norm Support Vector Machines2017 | Matematicko-fyzikální fakulta
- Sparse L1-norm quadratic surface support vector machine with Universum data2023 | Matematicko-fyzikální fakulta
- A lagrangian-based approach for universum twin bounded support vector machine with its applications2023 | Matematicko-fyzikální fakulta
- Universum parametric-margin ν-support vector machine for classification using the difference of convex functions algorithm2021 | Matematicko-fyzikální fakulta
- A Comparison of WorldView-2 and Landsat 8 Images for the Classification of Forests Affected by Bark Beetle Outbreaks Using a Support Vector Machine and a Neural Network: A Case Study in the Sumava Mountains2019 | Přírodovědecká fakulta, 1. lékařská fakulta, Matematicko-fyzikální fakulta
- Financial stability indicator predictability by support vector machines2012 | Fakulta sociálních věd
- Mapping vegetation communities of the Karkonosze National Park using APEX hyperspectral data and Support Vector Machines2014 | Přírodovědecká fakulta
- Statistical sex determination from craniometrics: Comparison of linear discriminant analysis, logistic regression, and support vector machines2014 | Přírodovědecká fakulta
- Sparse solution of least-squares twin multi-class support vector machine using l0 and lp-norm for classification and feature selection2023 | Matematicko-fyzikální fakulta
- Measurement of the inclusive t(t)over-bar production cross section in the lepton plus jets channel in pp collisions at SQUARE ROOTs=7 TeV with the ATLAS detector using support vector machines2023 | Matematicko-fyzikální fakulta
- Prospective Prediction of Thin-Cap Fibroatheromas from Baseline Virtual Histology Intravascular Ultrasound Data2015 | 1. lékařská fakulta
- Acoustic Assessment of Voice and Speech Disorders in Parkinson's Disease Through Quick Vocal Test2011 | 1. lékařská fakulta
- Evaluation of remote sensing methods and data for land cover classification: case studies of former military training areas Brdy and Ralsko2018 | Přírodovědecká fakulta
- Regional gray matter changes and age predict individual treatment response in Parkinson's disease2019 | 1. lékařská fakulta
- Predicting the Fission Yeast Protein Interaction Network2012 | Přírodovědecká fakulta
- Classification of first-episode psychosis using cortical thickness: A large multicenter MRI study2021 | Ústřední knihovna
- Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy2018 | Publikace bez příslušnosti k fakultě
- Unraveling corticobasal syndrome and alien limb syndrome with structural brain imaging2019 | 1. lékařská fakulta
- Improving clinical refractive results of cataract surgery by machine learning2019 | 3. lékařská fakulta
- Least squares approach to K-SVCR multi-class classification with its applications2022 | Matematicko-fyzikální fakulta
- Part of Speech Tagging in Urdu: Comparison of Machine and Deep Learning ApproachesPublikace bez příslušnosti k fakultě
- Disease-Specific Regions Outperform Whole-Brain Approaches in Identifying Progressive Supranuclear Palsy:A Multicentric MRI Study2017 | 1. lékařská fakulta, Fakulta tělesné výchovy a sportu
- FCM marker importance for MRD assessment in T-cell acute lymphoblastic leukemia: An AIEOP-BFM-ALL-FLOW study group report2024 | 2. lékařská fakulta
- Geometric morphometric and traditional methods for sex assessment using the posterior ilium2017 | Přírodovědecká fakulta, Matematicko-fyzikální fakulta
- Public’s Mental Health Monitoring via Sentimental Analysis of Financial Text Using Machine Learning TechniquesPublikace bez příslušnosti k fakultě
- Multi-center machine learning in imaging psychiatry: A meta-model approach2017 | Ústřední knihovna
- High-Accuracy Voice-Based Classification Between Patients With Parkinson's Disease and Other Neurological Diseases May Be an Easy Task With Inappropriate Experimental Design2017 | 1. lékařská fakulta