| _ | atr | _ |
|---|
| Adaptive Configuration and Control in an | atr | System |
| Adaptive Configuration and Control in an | atr | System |
| atr | |
| atr | - Oriented Objects, Vehicles, Aerial Images |
| atr | -- Clutter, Background Issues, Noise |
| atr | -- IR, Infra-Red, Thermal, Applications |
| atr | -- Model, Object Based Radar and SAR Recognition |
| atr | -- Multiple Sensors, Multiple Algorithms, Fusion |
| atr | -- Small Targets IR, Infra-Red, Thermal, Applications |
| atr | -- Sonar |
| atr | -- Survey, Review, Evaluation, General Discussions |
| atr | -- Targets, Radar, SAR Applications |
| atr | -- Vehicles, Aerial Images, Aircraft Detection, Recognition |
| atr | -- Vehicles, Aerial Images, Ship Detection |
| atr | -- Vehicles, Aerial Images, Vehicle Detection |
| atr | Applications, Automatic Target Recognition |
| atr | Performance Prediction with Feature Based Optimization |
| Attributed Scattering Centers for SAR | atr | |
| C-RISE: A Post-Hoc Interpretation Method of Black-Box Models for SAR | atr | |
| Clutter Invariant | atr | |
| Color Recognition by Learning: | atr | in Color Images |
| Complexity Analysis of | atr | Algorithms Based on Invariants |
| Comprehensive Survey on SAR | atr | in Deep-Learning Era, A |
| Context and Quasi-Invariants in | atr | with SAR Imagery |
| Context and Quasi-Invarinats in | atr | with SAR Imagery |
| Convolutional Neural Network Combined with Attributed Scattering Centers for SAR | atr | , A |
| Crucial feature capture and discrimination for limited training data SAR | atr | |
| D- | atr | for SAR Images Based on Deep Neural Networks |
| Detection Filters and Algorithm Fusion for | atr | |
| Dual-Band | atr | for Forward-Looking Infrared Images |
| Efficient | atr | Using Compression |
| Empirical Evaluation of Neural, Statistical and Model-based Approaches to FLIR | atr | |
| Experimental Evaluation of FLIR | atr | Approaches-A Comparative Study |
| Fast K-NN Search for Robust | atr | Object Matching |
| Few-Shot SAR- | atr | Based on Instance-Aware Transformer |
| FLIR | atr | Using Location Uncertainty |
| Focus of attention (FOA) identification from compressed video for automatic target recognition ( | atr | ) |
| Framework for High-Resolution Mapping of Soil Organic Matter (SOM) by the Integration of Fourier Mid-Infrared Attenuation Total Reflectance Spectroscopy (FTIR- | atr | ), Sentinel-2 Images, and DEM Derivatives, A |
| Hierarchical Fusion of Convolutional Neural Networks and Attributed Scattering Centers with Application to Robust SAR | atr | |
| High probability of detection, low false alarm multisensor | atr | |
| Hilbert-Schmidt Lower Bounds for Estimators on M | atr | ix Lie Groups for ATR |
| image metric-based | atr | performance prediction testbed, An |
| Integrated Use of 3-D Site Models and | atr | in SAR Image Exploitation |
| Mavis: A Special-Purpose Neural Computational System for | atr | |
| MFFA-SARNET: Deep Transferred Multi-Level Feature Fusion Attention Network with Dual Optimized Loss for Small-Sample SAR | atr | |
| Model-Based Automatic Target Recognition ( | atr | ) System for Forward-Looking Groundbased and Airborne Imaging Laser Radars (Ladar) |
| Model-Based SAR | atr | System |
| Multiclass SAR | atr | Using Shift-Invariant Correlation Filters |
| Multisensor | atr | and Identification of Friend or Foe Using MLANS |
| Neural networks for | atr | parameters adaptation |
| Novel | atr | Classifier Exploiting Pose Estimation, A |
| Overview of a Self-Adaptive | atr | System via Context-Based Configuration and Control |
| Project Summary: Context and Quasi-Invariants in | atr | |
| Robust Sonar | atr | Through Bayesian Pose-Corrected Sparse Classification |
| Robust Thermophysics-Based Interpretation of Radiometrically Uncalibrated IR Images for | atr | and Site Change Detection |
| SAR | atr | of Ground Vehicles Based on ESENet |
| SAR | atr | of Ground Vehicles Based on LM-BN-CNN |
| SAR- | atr | with knowledge hierarchy division and information dissemination networks |
| SARCASTIC v2.0: High-Performance SAR Simulation for Next-Generation | atr | Systems |
| Semi-Supervised SAR | atr | Framework with Transductive Auxiliary Segmentation |
| Semisupervised Learning-Based SAR | atr | via Self-Consistent Augmentation |
| Simultaneous multitarget detection and false alarm mitigation algorithm for the Predator UAV TESAR | atr | system |
| Sparse Signal Models for Data Augmentation in Deep Learning | atr | |
| SPIE -- Mapping, | atr | |
| Sub-Aperature Extensions to the Flexible Histogram Approach for SAR | atr | |
| Survey of | atr | Research and Development at HNC Software Inc. |
| Survey of IU and | atr | Research at ITT and UIC |
| Systolic Array for Acceleration of Template Based | atr | |
| Target Detection in Foveal | atr | Systems |
| Target Reconstruction Based on 3-D Scattering Center Model for Robust SAR | atr | |
| Target Reconstruction Based on Attributed Scattering Centers with Application to Robust SAR | atr | |
| VARTAC: A Foveal Active Vision | atr | System |
| When Deep Learning Meets Multi-Task Learning in SAR | atr | : Simultaneous Target Recognition and Segmentation |
73 for atr