Instruct: Given the title of a scientific paper, retrieve paper titles that are cited by the given paper
Query: Super-resolution of medical image using representation learning
Image Super-Resolution Via Sparse Representation
Large Receptive Field Networks for High-Scale Image Super-Resolution
Low-Rank Total Variation for Image Super-Resolution
Bayesian image super-resolution, continued
A Survey on Various Techniques of Super Resolution Imaging
Single Image Super-Resolution via Non Sub-sample Contourlet Transform based Learning and a Gabor Prior
Fast and Accurate Single Image Super-Resolution via Information Distillation Network
Robust super-resolution
Deeply-Recursive Convolutional Network for Image Super-Resolution
Deep Residual Network for Joint Demosaicing and Super-Resolution
Recovering Realistic Texture in Image Super-Resolution by Deep Spatial Feature Transform
Deep Network Cascade for Image Super-resolution
Low-Complexity Single-Image Super-Resolution based on Nonnegative Neighbor Embedding
Sparse depth super resolution
Coupled Deep Autoencoder for Single Image Super-Resolution
Image Super-Resolution Using Dense Skip Connections
Single image super-resolution using Gaussian process regression
Joint Dictionary Learning for Example-based Image Super-resolution
Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings
Super-Resolution Reconstruction of Image Sequences
Deep Adaptive Feature Embedding with Local Sample Distributions for Person Re-identification
Twin gate, vertical slit FET (VeSFET) for highly periodic layout and 3D integration
Learning to Estimate 3D Human Pose and Shape from a Single Color Image
Forensic Image Inspection Assisted by Deep Learning
Learning to Sense Sparse Signals: Simultaneous Sensing Matrix and Sparsifying Dictionary Optimization