Computer Science
Active Learning
16%
Artificial Intelligence
33%
Attention (Machine Learning)
12%
Bidirectional Long Short-Term Memory Network
8%
Blockchain
22%
Classification Accuracy
14%
Classification Models
10%
Comparative Analysis
12%
Convolutional Neural Network
54%
Data Augmentation
16%
Decision Tree
10%
Decision-Making
18%
Deep Learning Method
100%
Deep Learning Model
36%
Deep Neural Network
19%
Deep Transfer Learning
9%
Digital Twin
12%
Early Detection
11%
Ensemble Learning
14%
Experimental Result
15%
Explainable Artificial Intelligence
18%
Extreme Gradient Boosting
17%
Feature Extraction
33%
Feature Fusion
11%
Feature Selection
20%
Federated Learning
9%
Gait Recognition
11%
Gradient Boosting
9%
Image Classification
11%
Image Processing
12%
Internet-Of-Things
63%
k-Nearest Neighbors Algorithm
9%
Leaning Parameter
14%
Learning Approach
18%
Learning System
77%
Logistic Regression
11%
Long Short-Term Memory Network
18%
Machine Learning
82%
Machine Learning Algorithm
16%
Machine Learning Approach
11%
Machine Learning Technique
8%
Neural Network
10%
Quantum Computing
9%
Random Decision Forest
22%
Representation Learning
13%
SHapley Additive exPlanation
10%
Smart City
11%
Superior Performance
10%
Transfer Learning
36%
Tumor Detection
9%
Engineering
Artificial Intelligence
16%
Blockchain
5%
Component Analysis
5%
Computervision
6%
Convolutional Neural Network
15%
Deep Learning Method
52%
Factor of Safety
8%
Feature Extraction
19%
Gait Analysis
6%
Gait Recognition
11%
Image Classification
6%
Image Processing
8%
Internet-Of-Things
12%
Learning Approach
7%
Learning System
19%
Machine Learning Algorithm
15%
Machine Learning Technique
5%
Metrics
7%
Principal Component
6%
Quantum Computation
7%
Random Forest
7%
Rock Slope
9%
Slope Failure
6%
Smart City
6%
Transfer Learning
15%
