Index for savc

Savc, M.[Martin] Co Author Listing * Combinational illumination estimation method based on image-specific PCA filters and support vector regression
Includes: Savc, M.[Martin] Šavc, M.[Martin]

Savchenko, A. Co Author Listing * Efficient Statistical Face Recognition Using Trigonometric Series and CNN Features

Savchenko, A.V.[Andrey V.] Co Author Listing * Deep Convolutional Neural Networks and Maximum-Likelihood Principle in Approximate Nearest Neighbor Search
* Directed enumeration method in image recognition
* Maximum-likelihood approximate nearest neighbor method in real-time image recognition
* Neural Networks Compression for Language Modeling
* Nonlinear Transformation of the Distance Function in the Nearest Neighbor Image Recognition
* Optimal Greedy Approximate Nearest Neighbor Method in Statistical Pattern Recognition, An
* Semi-automated Speaker Adaptation: How to Control the Quality of Adaptation?
* Towards the creation of reliable voice control system based on a fuzzy approach
Includes: Savchenko, A.V.[Andrey V.] Savchenko, A.V.
8 for Savchenko, A.V.

Savchenko, E. Co Author Listing * Vega-constellation Tools To Analize Hyperspectral Images

Savchenko, L.V.[Liudmila V.] Co Author Listing * Towards the creation of reliable voice control system based on a fuzzy approach

Savchenko, V.[Vladimir] Co Author Listing * Interactive visualization of multi-layered clothing

Savchina, E.I. Co Author Listing * Content Preserving Watermarking for Medical Images Using Shearlet Transform and SVD

Savchynskyy, B.[Bogdan] Co Author Listing * bundle approach to efficient MAP-inference by Lagrangian relaxation, A
* Character templates learning for textual images recognition as an example of learning in structural recognition
* Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems, A
* Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems, A
* Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction
* Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems, A
* Evaluation of a First-Order Primal-Dual Algorithm for MRF Energy Minimization
* Getting Feasible Variable Estimates from Infeasible Ones: MRF Local Polytope Study
* Global Hypothesis Generation for 6D Object Pose Estimation
* Inferring M-Best Diverse Labelings in a Single One
* InstanceCut: From Edges to Instances with MultiCut
* Joint Training of Generic CNN-CRF Models with Stochastic Optimization
* MAP-Inference for Highly-Connected Graphs with DC-Programming
* Maximum Persistency via Iterative Relaxed Inference in Graphical Models
* Maximum persistency via iterative relaxed inference with graphical models
* MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models
* MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation
* Multicuts and Perturb and MAP for Probabilistic Graph Clustering
* Partial Optimality by Pruning for MAP-Inference with General Graphical Models
* Partial Optimality via Iterative Pruning for the Potts Model
* Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts
* Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching, A
* study of Nesterov's scheme for Lagrangian decomposition and MAP labeling, A
Includes: Savchynskyy, B.[Bogdan] Savchynskyy, B.
23 for Savchynskyy, B.

Index for "s"


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