Keyphrases
3D Shape
34%
Back-projection
26%
Compressed Sensing
22%
Compressive Sampling Matching Pursuit (CoSaMP)
37%
Convolutional Neural Network
48%
Convolutional Sparse Coding
20%
Cosparse
26%
Cosparse Analysis Model
24%
Deep Learning
90%
Deep Learning Methods
32%
Deep Neural Network
100%
Denoising
34%
Dictionary
46%
Dictionary Learning
20%
Distributed Acoustic Sensing
21%
Few-shot
50%
Few-shot Classification
20%
Few-shot Learning
24%
Gaussian Denoising
20%
Generalization Error
24%
Generative Adversarial Networks
55%
Greedy Algorithm
20%
Greedy Method
20%
Image Denoising
30%
Image Reconstruction
24%
Inverse Problem
43%
Labeled Data
22%
Light Field
20%
Motion Deblurring
20%
Neural Network
60%
Neural Radiance Field (NeRF)
20%
Oracle
23%
Performance Guarantee
26%
Phase Coding
37%
Point Cloud
46%
Poisson
20%
Poisson Denoising
25%
Popular
29%
Reflector
20%
Sparse Recovery
31%
Sparse Representation
34%
Sparsity
43%
Sparsity Basis
30%
Spatiotemporal
20%
Stein's Unbiased Risk Estimate
27%
Super-resolution
21%
Training Data
29%
Transfer Learning
22%
Unseen
38%
Unsupervised Learning
30%
Computer Science
Adversarial Machine Learning
32%
Analysis Model
30%
Annotation
17%
Approximation (Algorithm)
24%
Art Performance
19%
Backprojection
29%
Compressed Sensing
26%
Compressive Sampling
27%
Computer Vision
20%
Convolutional Neural Network
54%
de-noising
94%
Deep Learning Method
88%
Deep Learning Model
16%
Deep Neural Network
93%
Dictionary Learning
30%
Few-Shot Learning
31%
Gaussian White Noise
22%
Generalization Error
24%
Generative Adversarial Networks
52%
Generative Model
16%
Gradient Descent
20%
Greedy Algorithm
17%
image denoising
28%
Image Inpainting
16%
Image Processing
36%
Image Restoration
20%
Image Segmentation
17%
Image Synthesis
26%
Inverse Problem
65%
Jacobian Matrix
16%
Language Modeling
24%
Least Squares Method
21%
Matching Pursuit
23%
Neural Network
77%
Neural Radiance Field
20%
Performance Guarantee
24%
Point Cloud
52%
Pursuit Algorithm
18%
Regularization
47%
Residual Neural Network
15%
Risk Estimator
20%
Self-Supervised Learning
17%
Sparse Representation
32%
Sparsity
56%
super resolution
37%
Total Variation
18%
Trained Network
16%
Training Data
20%
Transfer Learning
15%
Unsupervised Learning
16%
