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Found 7 papers, 2 papers with code
BS-Diff: Effective Bone Suppression Using Conditional Diffusion Models from Chest X-Ray Images
As a remedial measure, bone suppression techniques have been introduced.
View-Disentangled Transformer for Brain Lesion Detection
Deep neural networks (DNNs) have been widely adopted in brain lesion detection and segmentation.
Learning to Prove Trigonometric Identities
We define the normalized form of trigonometric identities, design a set of rules for the proof and put forward a method which can generate theoretically infinite trigonometric identities.
Mixed Noise Removal with Pareto Prior
To address this problem, we exploit the Pareto distribution as the priori of the weighting matrix, based on which an accurate and robust weight estimator is proposed for mixed noise removal.
Learning Cluster Structured Sparsity by Reweighting
Recently, the paradigm of unfolding iterative algorithms into finite-length feed-forward neural networks has achieved a great success in the area of sparse recovery.
CRNet: Image Super-Resolution Using A Convolutional Sparse Coding Inspired Network
Convolutional Sparse Coding (CSC) has been attracting more and more attention in recent years, for making full use of image global correlation to improve performance on various computer vision applications.
Image Super-Resolution via RL-CSC: When Residual Learning Meets Convolutional Sparse Coding
We extend LISTA to its convolutional version and build the main part of our model by strictly following the convolutional form, which improves the network's interpretability.
Ranked #33 on
Image Super-Resolution
on BSD100 - 4x upscaling
