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De-aliasing

De-aliasing is the problem of recovering the original high-frequency information that has been aliased during the acquisition of an image.

Papers

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Showing 1–22 of 22 papers

TitleStatusHype
Spectral-Refiner: Accurate Fine-Tuning of Spatiotemporal Fourier Neural Operator for Turbulent FlowsCode2
When Semantic Segmentation Meets Frequency AliasingCode1
Adaptive Diffusion Priors for Accelerated MRI ReconstructionCode1
A Plug-and-Play Approach to Multiparametric Quantitative MRI: Image Reconstruction using Pre-Trained Deep DenoisersCode1
Complementary Time-Frequency Domain Networks for Dynamic Parallel MR Image ReconstructionCode1
Compressive MR Fingerprinting reconstruction with Neural Proximal Gradient iterationsCode1
HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite ImageryCode1
HighRes-net: Multi-Frame Super-Resolution by Recursive FusionCode1
Deep learning based spatial aliasing reduction in beamforming for audio capture—0
EMWaveNet: Physically Explainable Neural Network Based on Electromagnetic Propagation for SAR Target Recognition—0
eGAD! double descent is explained by Generalized Aliasing Decomposition—0
DARCS: Memory-Efficient Deep Compressed Sensing Reconstruction for Acceleration of 3D Whole-Heart Coronary MR Angiography—0
A plug-and-play synthetic data deep learning for undersampled magnetic resonance image reconstruction—0
A Deep Learning Approach for Parallel Imaging and Compressed Sensing MRI Reconstruction—0
Multi-branch Cascaded Swin Transformers with Attention to k-space Sampling Pattern for Accelerated MRI Reconstruction—0
Seeking Common Ground While Reserving Differences: Multiple Anatomy Collaborative Framework for Undersampled MRI Reconstruction—0
Temporal Embeddings and Transformer Models for Narrative Text Understanding—0
RODEO: Robust DE-aliasing autoencOder for Real-time Medical Image Reconstruction—0
Model-based Convolutional De-Aliasing Network Learning for Parallel MR Imaging—0
Can learning from natural image denoising be used for seismic data interpolation?Code0
Real-time Cardiovascular MR with Spatio-temporal Artifact Suppression using Deep Learning - Proof of Concept in Congenital Heart Disease—0
Deep De-Aliasing for Fast Compressive Sensing MRI—0
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