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