Zemek, F.
* 2016: Evaluating The Potential Of Satellite Hyperspectral Resurs-p Data For Forest Species Classification
* 2016: Visualisation Of Dependencies Between City Structure And Thermal Behaviour In Brno
* 2017: Improved Temperature and Emissivity Separation Algorithm for Multispectral and Hyperspectral Sensors
* 2018: Comparison of Global and Continental Land Cover Products for Selected Study Areas in South Central and Eastern European Region
* 2019: High-Performance Airborne Imaging Spectrometer HyPlant: From Raw Images to Top-of-Canopy Reflectance and Fluorescence Products: Introduction of an Automatized Processing Chain, The
* 2023: Flying Laboratory of Imaging Systems: Fusion of Airborne Hyperspectral and Laser Scanning for Ecosystem Research
Includes: Zemek, F. Zemek, F.[Frantisek] Zemek, F.[František]
Zemel, R.
* 2015: Aligning Books and Movies: Towards Story-Like Visual Explanations by Watching Movies and Reading Books
* 2015: Guest Editors' Introduction: Special Section on Higher Order Graphical Models in Computer Vision
* 2023: SurfsUp: Learning Fluid Simulation for Novel Surfaces
Includes: Zemel, R. Zemel, R.[Richard]
Zemel, R.S.[Richard S.]
* 1993: Developing Population Codes for Object Instantiation Parameters
* 1993: Unsupervised Learning of Object Models
* 1995: Helmholtz Machine, The
* 2004: Multiscale conditional random fields for image labeling
* 2006: Automated Detection of Unusual Events on Stairs
* 2006: Learning and Incorporating Top-Down Cues in Image Segmentation
* 2008: Latent topic random fields: Learning using a taxonomy of labels
* 2008: Learning Flexible Features for Conditional Random Fields
* 2008: Learning stick-figure models using nonparametric Bayesian priors over trees
* 2008: Unsupervised Learning of Skeletons from Motion
* 2009: Automated Detection of Unusual Events on Stairs
* 2010: Learning Articulated Structure and Motion
* 2013: Exploring Compositional High Order Pattern Potentials for Structured Output Learning
* 2014: Topic Modeling of Multimodal Data: An Autoregressive Approach
* 2015: Neural Autoregressive Approach to Attention-based Recognition, A
* 2017: Efficient Multiple Instance Metric Learning Using Weakly Supervised Data
* 2017: End-to-End Instance Segmentation with Recurrent Attention
* 2017: Learning to generate images with perceptual similarity metrics
Includes: Zemel, R.S.[Richard S.] Zemel, R.S.
18 for Zemel, R.S.
Zemen, T.
* 2015: Serial subtractive deconvolution algorithms for time-domain ultra wide band in-vehicle channel sounding
* 2015: Time- and Frequency-Varying K -Factor of Non-Stationary Vehicular Channels for Safety-Relevant Scenarios
Zemene Mequanint, E.[Eyasu]
* 2014: Poisoning Complete-Linkage Hierarchical Clustering
Zemene, E.[Eyasu]
* 2015: Path-Based Dominant-Set Clustering
* 2016: Constrained dominant sets for retrieval
* 2016: Interactive Image Segmentation Using Constrained Dominant Sets
* 2016: Multi-object tracking using dominant sets
* 2016: Simultaneous clustering and outlier detection using dominant sets
* 2019: Large-Scale Image Geo-Localization Using Dominant Sets
* 2019: Multi-target Tracking in Multiple Non-overlapping Cameras Using Fast-Constrained Dominant Sets
7 for Zemene, E.
Zemerly, M.J.
* 2005: Image Compression Using Adaptive Variable Degree Variable Segment Length Chebyshev Polynomials
* 2015: Illumination Invariant Robust Likelihood Estimator for Particle Filtering Based Target Tracking
* 2018: Balancing Incident and Ambient Light for Illumination Compensation in Video Applications
* 2018: Robust Likelihood Model for Illumination Invariance in Particle Filtering
Includes: Zemerly, M.J. Zemerly, M.J.[M. Jamal]