Durr, J.[Jasmin]
* 2013: Discriminative Detection and Alignment in Volumetric Data
* 2014: Accurate Detection in Volumetric Images Using Elastic Registration Based Validation
Includes: Durr, J.[Jasmin] Dürr, J.[Jasmin] (Maybe also Duerr, J.)
Durr, N.J.
* 2018: Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Training
* 2020: Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Images
* 2020: EndoL2H: Deep Super-Resolution for Capsule Endoscopy
* 2020: GANPOP: Generative Adversarial Network Prediction of Optical Properties From Single Snapshot Wide-Field Images
Durr, O.[Oliver]
* 2021: Deep transformation models: Tackling complex regression problems with neural network based transformation models
* 2022: Deep and interpretable regression models for ordinal outcomes
Includes: Durr, O.[Oliver] Dürr, O.[Oliver] (Maybe also Duerr, O.)
Durrani, M.N.
* 2020: Ensemble Learning Using Bagging And Inception-V3 For Anomaly Detection In Surveillance Videos
Durrani, S.
* 2016: Gauss-Legendre Sampling on the Rotation Group
Durrani, T.S.
* 1987: Goal Driven Parameter Evaluation for the Detection of Objects in SAR Data
* 1994: Multi-resolution based algorithms for low bit-rate image coding
* 1995: intelligent perception system for food quality inspection using color analysis, An
* 2000: Framework for Multi-Scale and Hybrid RKHS-Based Approximators, A
* 2002: RKHS Interpolator-Based Graph Matching Algorithm, A
* 2004: Efficient Implementation of Accurate Geometric Transformations for 2-D and 3-D Image Processing
* 2007: New Divergence Measure for Medical Image Registration, A
* 2018: Bilateral Convolutional Activations Encoded with Fisher Vectors for Scene Character Recognition
* 2020: Multi-Evidence and Multi-Modal Fusion Network for Ground-Based Cloud Recognition
* 2020: Multimodal Ground-Based Remote Sensing Cloud Classification via Learning Heterogeneous Deep Features
* 2021: Part-guided graph convolution networks for person re-identification
* 2022: Cross-Domain Person Re-Identification Using Heterogeneous Convolutional Network
* 2022: Ground-Based Remote Sensing Cloud Classification via Context Graph Attention Network
* 2022: Throughput Maximization for RIS-UAV Relaying Communications
* 2023: Cross-modality person re-identification using hybrid mutual learning
* 2023: Integration graph attention network and multi-centre constrained loss for cross-modality person re-identification
* 2023: Integration graph attention network and multi-centre constrained loss for cross-modality person re-identification
* 2024: Completed Part Transformer for Person Re-Identification
Includes: Durrani, T.S. Durrani, T.S.[Tariq S.]
18 for Durrani, T.S.
Durrant Whyte, H.F.
* 1987: Consistent Integration and Propagation of Disparate Sensor Observations
* 1987: Sensor Models and Multisensor Integration
* 1988: On Uncertain Geometry in Robotics
* 1988: Sensor Models and Multisensor Integration
* 1990: Bayesian Approach to Optimal Sensor Placement, A
* 1990: Integration, Coordination and Control of Multi-Sensor Robot Systems
* 1991: Mobile Robot Location by Tracking Geometric Beacons
* 1992: Directed Sonar Sensing for Mobile Robot Navigation
* 1992: Dynamic Map Building for an Autonomous Mobile Robot
* 1993: Decentralized Bayesian Algorithm for Identification of Tracked Targets, A
* 1993: Fully Decentralized Multi-Sensor System for Tracking and Surveillance, A
* 1994: Where am I? A Tutorial on Mobile Vehicle Localization
* 1998: Map-Building and Map-Based Localization in an Underground-Mine by Statistical Pattern Matching
* 2001: Solution to the Simultaneous Location and Map Building (SLAM) Problem, A
* 2006: Data Fusion in Sensor Networks
* 2006: Novel Visual Perception Framework, A
* 2007: Camera calibration for miniature, low-cost, wide-angle imaging systems
* 2007: optical navigation sensor for micro aerial vehicles, An
Includes: Durrant Whyte, H.F. Durrant-Whyte, H.F. Durrant-Whyte, H.F.[Hugh F.]
18 for Durrant Whyte, H.F.
Durrant, A.[Aiden]
* 2022: Hyperspherically regularized networks for self-supervision
Durrant, R.J.[Robert John]
* 2010: Bound on the Performance of LDA in Randomly Projected Data Spaces, A
* 2012: tight bound on the performance of Fisher's linear discriminant in randomly projected data spaces, A
* 2018: Maximum Gradient Dimensionality Reduction
Includes: Durrant, R.J.[Robert John] Durrant, R.J.
Durrieu de Madron, X.[Xavier]
* 2020: Glider-Based Active Acoustic Monitoring of Currents and Turbidity in the Coastal Zone
Durrieu, S.
* 2007: Processing Full-Waveform Lidar Data: Modelling Raw signals
* 2015: Discrete Anisotropic Radiative Transfer (DART 5) for Modeling Airborne and Satellite Spectroradiometer and LIDAR Acquisitions of Natural and Urban Landscapes
* 2018: Enhanced Measurements of Leaf Area Density with T-LiDAR: Evaluating and Calibrating the Effects of Vegetation Heterogeneity and Scanner Properties
* 2020: Scan Angle Impact on Lidar-derived Metrics Used in ABA Models for Prediction of Forest Stand Characteristics: A Grid Based Analysis
* 2022: investigation into lidar scan angle impacts on stand attribute predictions in different forest environments, An
Includes: Durrieu, S. Durrieu, S.[Sylvie]
Durrleman, S.
* 2011: Statistical Model for Quantification and Prediction of Cardiac Remodelling: Application to Tetralogy of Fallot, A
* 2013: Sparse Adaptive Parameterization of Variability in Image Ensembles
* 2013: Toward a Comprehensive Framework for the Spatiotemporal Statistical Analysis of Longitudinal Shape Data
* 2015: Bayesian Mixed Effect Atlas Estimation with a Diffeomorphic Deformation Model
* 2016: How to Build an Average Model When Samples are Variably Incomplete? Application to Fossil Data
* 2016: Parsimonious Approximation of Streamline Trajectories in White Matter Fiber Bundles
* 2016: Spatio-Temporal Shape Analysis of Cross-Sectional Data for Detection of Early Changes in Neurodegenerative Disease
* 2018: Double Diffeomorphism: Combining Morphometry and Structural Connectivity Analysis
* 2018: Geodesic Discriminant Analysis for Manifold-Valued Data
* 2018: Learning Distributions of Shape Trajectories from Longitudinal Datasets: A Hierarchical Model on a Manifold of Diffeomorphisms
* 2018: Sub-Riemannian Modular Framework for Diffeomorphism-Based Analysis of Shape Ensembles, A
* 2019: Auto-Encoding Meshes of any Topology with the Current-Splatting and Exponentiation Layers
* 2020: Learning the Clustering of Longitudinal Shape Data Sets into a Mixture of Independent or Branching Trajectories
* 2020: Learning the spatiotemporal variability in longitudinal shape data sets
* 2021: Gaussian Graphical Model Exploration and Selection in High Dimension Low Sample Size Setting
Includes: Durrleman, S. Durrleman, S.[Stanley]
15 for Durrleman, S.