Kunc, D.[Dominika]
* 2024: Ethical Considerations and Checklist for Affective Research With Wearables
Kunchala, A.[Anil]
* 2021: SMPL-Based 3D Pedestrian Pose Prediction
* 2023: Towards A Framework for Privacy-Preserving Pedestrian Analysis
Kunchev, R.
* 1996: Three Dimensional Computer Vision for Computer Design and Manufacturing Applications
Kuncheva, L.I.[Ludmila I.]
* 1992: critical comment on the paper designing of classification procedures with the use of equality and difference operators, A
* 1994: two-level classification scheme trained by a fuzzy neural network, A
* 1995: Experimental investigation on editing for the k-NN rule through a genetic algorithm
* 1995: On feature selection via rough sets
* 1996: RBF Network with Tunable Function Shape, An
* 1997: Fitness Functions in Editing K-NN Reference Set by Genetic Algorithms
* 1999: Nearest neighbor classifier: Simultaneous editing and feature selection
* 2000: Is Independence Good for Combining Classifiers?
* 2001: Decision templates for multiple classifier fusion: An Experimental Comparison
* 2002: Generating classifier outputs of fixed accuracy and diversity
* 2002: Switching between selection and fusion in combining classifiers: An Experiment
* 2002: Theoretical Study on Six Classifier Fusion Strategies, A
* 2003: Limits on the Majority Vote Accuracy in Classifier Fusion
* 2003: Measures of Diversity in Classifier Ensembles and Their Relationship with the Ensemble Accuracy
* 2005: Using diversity measures for generating error-correcting output codes in classifier ensembles
* 2006: Evaluation Measure of Image Segmentation Based on Object Centres, An
* 2006: Evaluation of Stability of k-Means Cluster Ensembles with Respect to Random Initialization
* 2006: On the optimality of Naïve Bayes with dependent binary features
* 2006: ROC curves and video analysis optimization in intestinal capsule endoscopy
* 2006: Rotation Forest: A New Classifier Ensemble Method
* 2008: Adaptive Learning Rate for Online Linear Discriminant Classifiers
* 2008: case-study on naive labelling for the nearest mean and the linear discriminant classifiers, A
* 2008: Combining Online Classification Approaches for Changing Environments
* 2008: Error-Dependency Relationships for the Naïve Bayes Classifier with Binary Features
* 2008: Linear Discriminant Classifier (LDC) for Streaming Data with Concept Drift
* 2010: Learn++.MF: A random subspace approach for the missing feature problem
* 2010: On-Line fMRI Data Classification Using Linear and Ensemble Classifiers
* 2010: Random Subspace Ensembles for fMRI Classification
* 2012: Naive random subspace ensemble with linear classifiers for real-time classification of fMRI data
* 2012: PCA feature extraction for change detection in multidimensional unlabelled streaming data
* 2014: Occlusion Handling via Random Subspace Classifiers for Human Detection
* 2014: On Optimum Thresholding of Multivariate Change Detectors
* 2014: spatial discrepancy measure between voxel sets in brain imaging, A
* 2014: Who Is Missing? A New Pattern Recognition Puzzle
* 2017: Comparing keyframe summaries of egocentric videos: Closest-to-centroid baseline
* 2017: Restricted set classification: Who is there?
* 2018: Budget-Constrained Online Video Summarisation of Egocentric Video Using Control Charts
* 2018: Edited nearest neighbour for selecting keyframe summaries of egocentric videos
* 2018: On feature selection protocols for very low-sample-size data
* 2018: Restricted Set Classification with prior probabilities: A case study on chessboard recognition
* 2019: Classification and comparison of on-line video summarisation methods
Includes: Kuncheva, L.I.[Ludmila I.] Kuncheva, L.I. Kuncheva, L.I.[Ludmilla I.]
41 for Kuncheva, L.I.