Loog, M.[Marco]
Co Author Listing * Active learning using uncertainty information
* Automated classification of local patches in colon histopathology
* Automated Effect-Specific Mammographic Pattern Measures
* Bayesian Active Learning for Maximal Information Gain on Model Parameters
* benchmark and comparison of active learning for logistic regression, A
* Bicycle chain shape models
* Blur Invariant Image Priors
* Bony Structure Suppression in Chest Radiographs
* Class-Dependent Dissimilarity Measures for Multiple Instance Learning
* Classification of COPD with Multiple Instance Learning
* Clustering Based Method for Edge Detection in Hyperspectral Images, A
* Combining multi-scale dissimilarities for image classification
* Compact Representation of Multiscale Dissimilarity Data by Prototype Selection, A
* Conditional Linear Discriminant Analysis
* Constrained Log-Likelihood-Based Semi-supervised Linear Discriminant Analysis
* Contrastive Pessimistic Likelihood Estimation for Semi-Supervised Classification
* Dense iterative contextual pixel classification using Kriging
* Dimensionality Reduction by Canonical Contextual Correlation Projections
* Dimensionality reduction of image features using the canonical contextual correlation projection
* Dipping Phenomenon, The
* Dissimilarity-based detection of schizophrenia
* dissimilarity-based multiple instance learning approach for protein remote homology detection, A
* Does one rotten apple spoil the whole barrel?
* Editorial of the Special Issue on Multi-instance Learning in Pattern Recognition and Vision
* Effects of sampling skewness of the importance-weighted risk estimator on model selection.
* Efficient Feature Extraction Based on Regularized Uncorrelated Chernoff Discriminant Analysis
* Efficient Segmentation by Sparse Pixel Classification
* empirical investigation into the inconsistency of sequential active learning, An
* Enhancing Classifier Conservativeness and Robustness by Polynomiality
* Feature-Based Dissimilarity Space Classification
* FIDOS: A generalized Fisher based feature extraction method for domain shift
* Forming Different-Complexity Covariance-Model Subspaces through Piecewise-Constant Spectra for Hyperspectral Image Classification
* Gaussian process variance reduction by location selection
* Gaussian Scale Space from Insufficient Image Information
* Generalized null space uncorrelated Fisher discriminant analysis for linear dimensionality reduction
* Generic Blind Source Separation Using Second-Order Local Statistics
* Generic Maximum Likely Scale Selection
* Gradient Descent for Gaussian Processes Variance Reduction
* Implicitly Constrained Semi-supervised Linear Discriminant Analysis
* Improbability of Harris Interest Points, The
* Improved Generalization in Semi-Supervised Learning: A Survey of Theoretical Results
* Improving cross-validation based classifier selection using meta-learning
* Information theoretic preattentive saliency: A closed-form solution
* Integrating automatic and interactive brain tumor segmentation
* Jet Metric, The
* Learning Algorithms for Digital Reconstruction of Van Gogh's Drawings
* Linear Dimensionality Reduction via a Heteroscedastic Extension of LDA: The Chernoff Criterion
* Local Discriminant Analysis
* Local Fisher Embedding
* Metric learning by directly minimizing the k-NN training error
* Metric Learning in Dissimilarity Space for Improved Nearest Neighbor Performance
* Mode Seeking Clustering by KNN and Mean Shift Evaluated
* Multi-class Linear Feature Extraction by Nonlinear PCA
* Multi-scale convolutional neural network for pixel-wise reconstruction of Van Gogh's drawings
* Multi-spectral video endoscopy system for the detection of cancerous tissue
* Multiclass Linear Dimension Reduction by Weighted Pairwise Fisher Criteria
* Multiple instance learning with bag dissimilarities
* Multiple-instance learning as a classifier combining problem
* Network-Guided Group Feature Selection for Classification of Autism Spectrum Disorder
* On an alternative formulation of the Fisher criterion that overcomes the small sample problem
* On classification with bags, groups and sets
* On Combining Computer-Aided Detection Systems
* On Distributional Assumptions and Whitened Cosine Similarities
* On regularization parameter estimation under covariate shift
* On the behavior of spatial critical points under Gaussian blurring
* Optic Nerve Head Detection via Group Correlations in Multi-orientation Transforms
* Optimistic semi-supervised least squares classification
* Peaking Phenomenon in Semi-supervised Learning, The
* Pixel Position Regression: Application to Medical Image Segmentation
* Protein Remote Homology Detection Using Dissimilarity-Based Multiple Instance Learning
* Quantitative Comparison of Spot Detection Methods in Fluorescence Microscopy
* Recent submissions in linear dimensionality reduction and face recognition
* Resolution Learning in Deep Convolutional Networks Using Scale-Space Theory
* Respecting Domain Relations: Hypothesis Invariance for Domain Generalization
* Review of Domain Adaptation without Target Labels, A
* Robust domain-adaptive discriminant analysis
* Robust semi-supervised least squares classification by implicit constraints
* Scale selection for supervised image segmentation
* Scale-invariant sampling for supervised image segmentation
* Second Order Structure of Scale-Space Measurements
* SEDMI: Saliency based edge detection in multispectral images
* Segmentation of the Posterior Ribs in Chest Radiographs Using Iterated Contextual Pixel Classification
* Semi-supervised linear discriminant analysis through moment-constraint parameter estimation
* Shape of Learning Curves: A Review, The
* Single shot active learning using pseudo annotators
* Single- vs. multiple-instance classification
* Social Processes: Self-supervised Meta-learning Over Conversational Groups for Forecasting Nonverbal Social Cues
* soft-labeled self-training approach, A
* Static posterior probability fusion for signal detection: Applications in the detection of interstitial diseases in chest radiographs
* Stratified Generalized Procrustes Analysis
* study on semi-supervised dissimilarity representation, A
* Supervised localization of cell nuclei on TMA images
* Supervised Scale-Invariant Segmentation (and Detection)
* Supervised segmentation by iterated contextual pixel classification
* Support Blob Machines: The Sparsification of Linear Scale Space
* Template Matching via Densities on the Roto-Translation Group
* To Actively Initialize Active Learning
* Training data selection for cancer detection in multispectral endoscopy images
* Training of Templates for Object Recognition in Invertible Orientation Scores: Application to Optic Nerve Head Detection in Retinal Images
* Uncorrelated heteroscedastic LDA based on the weighted pairwise Chernoff criterion
* Using Multiscale Spectra in Regularizing Covariance Matrices for Hyperspectral Image Classification
* variance maximization criterion for active learning, A
* Weighted K-Nearest Neighbor revisited
Includes: Loog, M.[Marco] Loog, M.
103 for Loog, M.