Dragan, A.D.
* 2012: Herb 2.0: Lessons Learned From Developing a Mobile Manipulator for the Home
Dragan, K.[Krzysztof]
* 2016: 3D Reconstruction of Ultrasonic B-Scans for Nondestructive Testing of Composites
Draganov, D.[Deyan]
* 2021: Application of Seismic Interferometry by Multidimensional Deconvolution to Earthquake Data Recorded in Malarge, Argentina
Draganov, M.
* 1985: Computer Description and Decomposition of Scenes of 3D Line Drawings
Draganova, C.
* 2004: Comparing Different Classifiers for Automatic Age Estimation
Draghetti, S.[Stefano]
* 2022: Anatomy of Anthropically Controlled Natural Lagoons through Geophysical, Geological, and Remote Sensing Observations: The Valli Di Comacchio (NE Italy) Case Study
Draghici, A.[Adriana]
* 2018: Survey of Techniques for Automatically Sensing the Behavior of a Crowd, A
Draghici, S.[Sorin]
* 2007: System Biology Approach for the Steady-State Analysis of Gene Signaling Networks, A
Dragic, A.[Aleksandar]
* 2023: Impacts of Extreme Space Weather Events on September 6th, 2017 on Ionosphere and Primary Cosmic Rays
Dragicevic, S.[Suzana]
* 2013: Theme section Towards Intelligent Geoprocessing on the Web
* 2016: Geosimulation Approach for Data Scarce Environments: Modeling Dynamics of Forest Insect Infestation across Different Landscapes, A
* 2016: Geospatial big data handling theory and methods: A review and research challenges
* 2016: Geospatial Modelling Approach For 3d Urban Densification Developments
* 2016: Towards a voxel-based geographic automata for the simulation of geospatial processes
* 2017: Machine Learning Techniques for Modelling Short Term Land-Use Change
* 2019: Analyzing the Effects of Temporal Resolution and Classification Confidence for Modeling Land Cover Change with Long Short-Term Memory Networks
* 2019: Multidimensional Web GIS Approach for Citizen Participation on Urban Evolution
* 2020: Preface: Technical Commission IV on Spatial Information Science
* 2020: Representing Complex Evolving Spatial Networks: Geographic Network Automata
* 2021: Assessing the Similarities of 3d Simulation Model Outcomes
* 2022: Assessing the Impact of Neighborhood Size on Temporal Convolutional Networks for Modeling Land Cover Change
* 2022: Mitigating Imbalance of Land Cover Change Data for Deep Learning Models with Temporal and Spatiotemporal Sample Weighting Schemes
* 2023: Modelling Global Deforestation Using Spherical Geographic Automata Approach
Includes: Dragicevic, S.[Suzana] Dragicevic, S.
14 for Dragicevic, S.
Dragnea, V.
* 2005: Direct Shape from Isophotes
Drago, F.[Fredric]
* 2005: Locally Adaptive Chromatic Restoration Of Digitally Acquired Paintings
Drago, G.[Giacomo]
* 2013: CCMS: A Greedy Approach to Motif Extraction
Dragoi, I.C.
* 2014: Local-Prediction-Based Difference Expansion Reversible Watermarking
* 2015: On Local Prediction Based Reversible Watermarking
* 2016: Adaptive Pairing Reversible Watermarking
* 2018: Improved Pairwise Pixel-Value-Ordering for High-Fidelity Reversible Data Hiding
* 2018: Reversible Data Hiding in Encrypted Color Images Based on Vacating Room After Encryption and Pixel Prediction
Dragoja, M.
* 2005: Accuracy of 3D city models: EuroSDR comparison
Dragomir, A.[Anca]
* 2017: Convolutional Neural Networks for False Positive Reduction of Automatically Detected Cilia in Low Magnification TEM Images
* 2017: Enhancement of Cilia Sub-structures by Multiple Instance Registration and Super-Resolution Reconstruction
* 2019: K-Nets: Clustering through nearest neighbors networks
* 2022: Differential Impact of Autonomous Vehicle Malfunctions on Human Trust
Includes: Dragomir, A.[Anca] Dragomir, A.[Andrei]
Dragomirescu, D.[Daniela]
* 2005: Object Recognition System-on-Chip Using the Support Vector Machines
Dragomiretskiy, K.[Konstantin]
* 2015: Two-Dimensional Variational Mode Decomposition
* 2017: Two-Dimensional Compact Variational Mode Decomposition
* 2018: Variational Destriping in Remote Sensing Imagery: Total Variation with L1 Fidelity
Dragon, R.[Ralf]
* 2009: Reading from Scratch: A Vision-System for Reading Data on Micro-structured Surfaces
* 2010: NF-Features: No-Feature-Features for Representing Non-textured Regions
* 2010: View-invariant Fall Detection for Elderly in Real Home Environment
* 2011: Fingerprints for Machines: Characterization and Optical Identification of Grinding Imprints
* 2011: Towards Feature-Based Situation Assessment for Airport Apron Video Surveillance
* 2012: 3d Object Recognition and Pose Estimation for Multiple Objects Using Multi-Prioritized Ransac and Model Updating
* 2012: Multi-scale Clustering of Frame-to-Frame Correspondences for Motion Segmentation
* 2013: Robust Realtime Motion-Split-And-Merge for Motion Segmentation
* 2014: Ground Plane Estimation Using a Hidden Markov Model
* 2014: Motion Segmentation with Weak Labeling Priors
* 2014: Multi-view Tracking of Multiple Targets with Dynamic Cameras
* 2015: Weakly supervised motion segmentation with particle matching
* 2016: Dilemma First Search for effortless optimization of NP-hard problems
* 2016: Joint Tracking and Ground Plane Estimation
* 2016: Markov Chain Monte Carlo Cascade for Camera Network Calibration Based on Unconstrained Pedestrian Tracklets
* 2016: Tracking by switching state space models
Includes: Dragon, R.[Ralf] Dragon, R.
16 for Dragon, R.
Dragone, R.V.
* 2019: Hermite-Gaussian mode detection via convolution neural networks
Dragoni, A.[Alessio]
* 2021: IdroGEO: A Collaborative Web Mapping Application Based on REST API Services and Open Data on Landslides and Floods in Italy
Dragoni, A.F.[Aldo Franco]
* 2011: Continuous Learning in a Changing Environment, A
Dragoni, M.[Mauro]
* 2012: Electrocardiographic Signal Classification with Evolutionary Artificial Neural Networks
* 2017: Neural Word Embeddings Approach for Multi-Domain Sentiment Analysis, A
* 2018: OntoSenticNet: A Commonsense Ontology for Sentiment Analysis
* 2019: Ontology-Driven Food Category Classification in Images
Includes: Dragoni, M.[Mauro] Dragoni, M.
Dragosevic, M.[Marina]
* 2010: Critical infrastructure monitoring using high resolution SAR satellites
Dragosevic, M.V.
* 2012: Detection and Estimation With RADARSAT-2 Moving-Object Detection Experiment Modes
Dragotti, P.L.
* 2000: Compression of Multispectral Images by Three-Dimensional SPIHT Algorithm
* 2000: Wavelet Transform Footprints: Catching Singularities for Compression and Denoising
* 2001: Footprints and Edgeprints for Image Denoising and Compression
* 2001: On the Compression of Two-dimensional Piecewise Smooth Functions
* 2002: Directional wavelet transforms and frames
* 2003: Discrete multi-directional wavelet bases
* 2003: Filter banks for multiple description coding
* 2003: Sampling and interpolation of the plenoptic function
* 2004: Distributed compression of the plenoptic function
* 2005: Approximation Power of Directionlets
* 2005: Rate-Distortion Optimized Tree-Structured Compression Algorithms for Piecewise Polynomial Images
* 2006: Directionlets: Anisotropic Multidirectional Representation With Separable Filtering
* 2006: Distributed Acquisition and Image Super-Resolution Based on Continuous Moments from Samples
* 2006: Exact Local Reconstruction Algorithms for Signals with Finite Rate of Innovation
* 2006: Low-Rate Reduced Complexity Image Compression using Directionlets
* 2006: Tomographic Approach for Sampling Multidimensional Signals with Finite Rate of Innovation
* 2007: Distributed Compression of Multi-View Images using a Geometrical Coding Approach
* 2007: Local Feature Extraction for Image Super-Resolution
* 2007: Unsupervised extraction of coherent regions for image based rendering
* 2008: Subspace-based methods for image registration and super-resolution
* 2009: Exact Feature Extraction Using Finite Rate of Innovation Principles With an Application to Image Super-Resolution
* 2009: Geometry-Driven Distributed Compression of the Plenoptic Function: Performance Bounds and Constructive Algorithms
* 2009: Image restoration using a sparse quadtree decomposition representation
* 2010: closed-form expression for the bandwidth of the plenoptic function under finite field of view constraints, A
* 2010: E-spline sampling for precise and robust line-edge extraction
* 2010: Multiview image compression using a layer-based representation
* 2011: Adaptive plenoptic sampling
* 2011: Interactive multiview image coding
* 2012: Line-edge extraction based on E-spline acquisition model and a fast optimization algorithm
* 2012: Multiview Image Coding Using Depth Layers and an Optimized Bit Allocation
* 2013: Plenoptic Layer-Based Modeling for Image Based Rendering
* 2013: Transform coder identification with double quantized data
* 2013: Video recapture detection based on ghosting artifact analysis
* 2014: On the Spectrum of the Plenoptic Function
* 2014: Quadtree Structured Image Approximation for Denoising and Interpolation
* 2014: Robust image recapture detection using a K-SVD learning approach to train dictionaries of edge profiles
* 2014: Tilted layer-based modeling for enhanced light-field processing and image based rendering
* 2014: Wide-baseline image change detection
* 2015: Guaranteed Performance in the FRI Setting
* 2015: On the Reconstruction of Wavelet-Sparse Signals From Partial Fourier Information
* 2015: Sampling piecewise smooth signals and its application to image up-sampling
* 2016: FRESH: FRI-Based Single-Image Super-Resolution Algorithm
* 2016: Identification of Transform Coding Chains
* 2017: SRHRF+: Self-Example Enhanced Single Image Super-Resolution Using Hierarchical Random Forests
* 2018: DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction
* 2018: Photo Realistic Image Completion via Dense Correspondence
* 2019: Wavelet Domain Style Transfer for an Effective Perception-Distortion Tradeoff in Single Image Super-Resolution
* 2020: Deep Coupled ISTA Network for Multi-Modal Image Super-Resolution
* 2020: RADAR: Robust Algorithm for Depth Image Super Resolution Based on FRI Theory and Multimodal Dictionary Learning
* 2021: CU-Net+: Deep Fully Interpretable Network for Multi-Modal Image Restoration
* 2021: Deep Convolutional Neural Network for Multi-Modal Image Restoration and Fusion
* 2021: Joint Learning of 3D Lesion Segmentation and Classification for Explainable COVID-19 Diagnosis
* 2022: AI-Based Reconstruction for Fast MRI: A Systematic Review and Meta-Analysis
* 2022: Light-Field Microscopy for the Optical Imaging of Neuronal Activity: When model-based methods meet data-driven approaches
* 2022: Mixed X-Ray Image Separation for Artworks With Concealed Designs
* 2022: Multi-Modal Convolutional Dictionary Learning
* 2022: WINNet: Wavelet-Inspired Invertible Network for Image Denoising
* 2023: Sensing Diversity and Sparsity Models for Event Generation and Video Reconstruction from Events
Includes: Dragotti, P.L. Dragotti, P.L.[Pier Luigi] Dragotti, P.L.[Pier-Luigi]
58 for Dragotti, P.L.
Dragov, R.[Rangel]
* 2022: Phenotypic Traits Estimation and Preliminary Yield Assessment in Different Phenophases of Wheat Breeding Experiment Based on UAV Multispectral Images
* 2024: Preharvest Durum Wheat Yield, Protein Content, and Protein Yield Estimation Using Unmanned Aerial Vehicle Imagery and Pleiades Satellite Data in Field Breeding Experiments
Dragozi, E.[Eleni]
* 2014: Burned Area Mapping Using Support Vector Machines and the FuzCoC Feature Selection Method on VHR IKONOS Imagery
* 2014: Decision Fusion Based on Hyperspectral and Multispectral Satellite Imagery for Accurate Forest Species Mapping
* 2016: Exploring the Relationship between Burn Severity Field Data and Very High Resolution GeoEye Images: The Case of the 2011 Evros Wildfire in Greece
* 2021: Dead Fuel Moisture Content (DFMC) Estimation Using MODIS and Meteorological Data: The Case of Greece
Dragulin, I.
* 2016: Quantifying the accuracy of FRI-based LIDAR waveform analysis
Dragut, L.
* 2014: Automated parameterisation for multi-scale image segmentation on multiple layers
* 2014: Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imagery
* 2014: Quantitative evaluation of variations in rule-based classifications of land cover in urban neighbourhoods using WorldView-2 imagery
* 2016: Random forest in remote sensing: A review of applications and future directions
* 2020: Individual Tree-Crown Detection and Species Classification in Very High-Resolution Remote Sensing Imagery Using a Deep Learning Ensemble Model
Includes: Dragut, L. Dragut, L.[Lucian]
Dragut, L.D.
* 2006: Using digital photographs and object-based image analysis to estimate percent ground cover in vegetation plots
* 2010: Developing a Semantic Model of Glacial Landforms for Objectbased Terrain Classification: The Example of Glacial Cirques