Savc, M.[Martin]
* 2018: Combinational illumination estimation method based on image-specific PCA filters and support vector regression
Includes: Savc, M.[Martin] Šavc, M.[Martin]
Savchenko, A.
* 2018: Efficient Statistical Face Recognition Using Trigonometric Series and CNN Features
* 2020: Detection and Recognition of Food in Photo Galleries for Analysis of User Preferences
Includes: Savchenko, A. Savchenko, A.[Andrey]
Savchenko, A.V.
* 2012: Directed enumeration method in image recognition
* 2014: Nonlinear Transformation of the Distance Function in the Nearest Neighbor Image Recognition
* 2014: Semi-automated Speaker Adaptation: How to Control the Quality of Adaptation?
* 2015: Optimal Greedy Approximate Nearest Neighbor Method in Statistical Pattern Recognition, An
* 2015: Towards the creation of reliable voice control system based on a fuzzy approach
* 2017: Deep Convolutional Neural Networks and Maximum-Likelihood Principle in Approximate Nearest Neighbor Search
* 2017: Maximum-likelihood approximate nearest neighbor method in real-time image recognition
* 2017: Neural Networks Compression for Language Modeling
* 2019: User Modeling on Mobile Device Based on Facial Clustering and Object Detection in Photos and Videos
* 2020: Mobileemotiface: Efficient Facial Image Representations in Video-based Emotion Recognition on Mobile Devices
* 2020: New Sport Teams Logo Dataset for Detection Tasks, A
* 2022: Classifying Emotions and Engagement in Online Learning Based on a Single Facial Expression Recognition Neural Network
* 2022: MT-emotieffnet for Multi-task Human Affective Behavior Analysis and Learning from Synthetic Data
* 2022: Preference prediction based on a photo gallery analysis with scene recognition and object detection
* 2022: Video-based Frame-level Facial Analysis of Affective Behavior on Mobile Devices using EfficientNets
* 2023: EmotiEffNets for Facial Processing in Video-based Valence-Arousal Prediction, Expression Classification and Action Unit Detection
Includes: Savchenko, A.V. Savchenko, A.V.[Andrey V.]
16 for Savchenko, A.V.
Savchenko, E.
* 2016: Vega-constellation Tools To Analize Hyperspectral Images
Savchenko, L.V.[Liudmila V.]
* 2015: Towards the creation of reliable voice control system based on a fuzzy approach
* 2022: Classifying Emotions and Engagement in Online Learning Based on a Single Facial Expression Recognition Neural Network
Includes: Savchenko, L.V.[Liudmila V.] Savchenko, L.V.[Lyudmila V.]
Savchenko, V.[Vladimir]
* 2017: Interactive visualization of multi-layered clothing
Savchik, A.[Alex]
* 2022: NTIRE 2022 Challenge on Night Photography Rendering
Savchina, E.I.
* 2017: Content Preserving Watermarking for Medical Images Using Shearlet Transform and SVD
* 2019: Digital Watermarking of 3d Medical Visual Objects
Savchuk, S.[Stepan]
* 2023: Seasonal Variations Analysis of Permanent GNSS Station Time Series in the Central-East of Europe, The
* 2024: Python Software Tool for Diagnostics of the Global Navigation Satellite System Station (PS-NETM)-Reviewing the New Global Navigation Satellite System Time Series Analysis Tool
Savchynskyy, B.
* 2006: Character templates learning for textual images recognition as an example of learning in structural recognition
* 2008: MAP-Inference for Highly-Connected Graphs with DC-Programming
* 2010: MRF Inference by k-Fan Decomposition and Tight Lagrangian Relaxation
* 2011: Evaluation of a First-Order Primal-Dual Algorithm for MRF Energy Minimization
* 2011: study of Nesterov's scheme for Lagrangian decomposition and MAP labeling, A
* 2012: bundle approach to efficient MAP-inference by Lagrangian relaxation, A
* 2013: Comparative Study of Modern Inference Techniques for Discrete Energy Minimization Problems, A
* 2013: Getting Feasible Variable Estimates from Infeasible Ones: MRF Local Polytope Study
* 2013: Partial Optimality via Iterative Pruning for the Potts Model
* 2014: Partial Optimality by Pruning for MAP-Inference with General Graphical Models
* 2015: Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems, A
* 2015: Inferring M-Best Diverse Labelings in a Single One
* 2015: Maximum persistency via iterative relaxed inference with graphical models
* 2015: Probabilistic Correlation Clustering and Image Partitioning Using Perturbed Multicuts
* 2016: Joint Training of Generic CNN-CRF Models with Stochastic Optimization
* 2016: Multicuts and Perturb and MAP for Probabilistic Graph Clustering
* 2016: Partial Optimality by Pruning for MAP-Inference with General Graphical Models
* 2017: Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems, A
* 2017: Global Hypothesis Generation for 6D Object Pose Estimation
* 2017: InstanceCut: From Edges to Instances with MultiCut
* 2017: Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching, A
* 2018: Conditional Random Fields Meet Deep Neural Networks for Semantic Segmentation: Combining Probabilistic Graphical Models with Deep Learning for Structured Prediction
* 2018: Maximum Persistency via Iterative Relaxed Inference in Graphical Models
* 2018: MPLP++: Fast, Parallel Dual Block-Coordinate Ascent for Dense Graphical Models
* 2019: Discrete Graphical Models: An Optimization Perspective
* 2021: Fusion Moves for Graph Matching
* 2022: Comparative Study of Graph Matching Algorithms in Computer Vision, A
Includes: Savchynskyy, B. Savchynskyy, B.[Bogdan]
27 for Savchynskyy, B.
Savci, K.[Kubilay]
* 2021: Counter-Interception and Counter-Exploitation Features of Noise Radar Technology
* 2021: Low-PAPR Waveforms with Shaped Spectrum for Enhanced Low Probability of Intercept Noise Radars