Computer Science
Alternating Direction Method of Multipliers
10%
Annotation
54%
Approximation (Algorithm)
12%
Art Performance
14%
Automatic Segmentation
10%
Base Class
12%
Computer Vision
16%
Constrained Optimization
31%
Convolutional Neural Network
90%
Deep Learning Method
15%
Deep Learning Model
18%
Deep Neural Network
27%
Discriminator
12%
Domain Adaptation
32%
Equality Constraint
22%
Few-Shot Learning
11%
Foundation Model
28%
Generalizability
10%
Graph Cut
11%
Image Analysis
18%
Image Classification
18%
Image Segmentation
100%
Inequality Constraint
29%
Invariant Domain
10%
Knowledge Distillation
21%
Language Modeling
36%
Learning Approach
10%
Learning System
19%
Lesion Segmentation
11%
Machine Learning
19%
Medical Imaging
26%
Mutual Information
16%
Network Segmentation
65%
New-State
11%
Prompt Learning
10%
Recent Literature
13%
Regularization
20%
segmentation accuracy
18%
Segmentation Method
14%
Segmentation Task
16%
Semisupervised Learning
22%
Shannon Entropy
13%
Superior Performance
16%
Supervised Learning
17%
Transfer Learning
15%
Uncertainty Estimation
12%
Unlabeled Data
29%
Unsupervised Anomaly Detection
14%
Unsupervised Domain Adaptation
13%
Zero-Shot Learning
18%
Keyphrases
3D Convolutional Neural Network (3D CNN)
13%
Adaptation
23%
Adapter
15%
Attention Map
14%
Bladder Cancer
15%
Brain Image Segmentation
18%
Comprehensive Experiment
28%
Constrained Optimization
18%
Convolutional Neural Network
28%
Cross-entropy
24%
Deep Network
24%
Deep Neural Network
25%
Dice Similarity Coefficient
13%
Domain Adaptation
23%
Domain Shift
16%
Equality Constraints
16%
Few-shot
29%
Foundation Models
23%
Full Supervision
13%
Image Segmentation
29%
Inequality Constraints
28%
Knowledge Distillation
21%
Label Smoothing
33%
Linear Probe
19%
Logit
17%
Loss Function
16%
Magnetic Resonance Imaging
36%
Medical Image Analysis
15%
Medical Image Segmentation
41%
Miscalibration
18%
Organs at Risk
24%
Popular
39%
Publicly Available
21%
Radiotherapy
20%
Segmentation Accuracy
14%
Segmentation Network
51%
Segmentation Problem
23%
Semantic Segmentation
16%
Semi-supervised Segmentation
14%
Source Domain
19%
State-of-the-art Techniques
12%
Target Domain
28%
Transductive Inference
16%
U-Net
15%
Uncertainty Estimation
13%
Unlabeled Data
21%
Unsupervised Domain Adaptation
15%
Unsupervised Learning
17%
Vision-language Models
20%
Weakly Supervised Segmentation
26%
