Computer Science
Expert System
66%
Vehicle Detection
66%
Multicasting
66%
Experimental Result
66%
Level Architecture
50%
Fault Diagnosis
44%
Multicast Group
44%
Knowledge Acquisition
44%
Simulation Experiment
44%
Nash Equilibrium
33%
Based Vehicle Detection
33%
Audio Transmission
33%
Extraction Process
33%
Organization Unit
33%
Energy Detection
33%
Feature Extraction
33%
Mathematical Method
33%
Detection Algorithm
33%
Expert Knowledge
33%
Software Quality
33%
Classification Algorithm
33%
Fuzzy Logic
33%
multi agent
33%
Interest Management
33%
Operational Effectiveness
33%
Traffic Parameter
33%
Feature Vector
33%
Classifier
33%
Control Algorithm
33%
Back Propagation Neural Network
33%
Frame Similarity
33%
Traffic Condition
33%
Inference System
33%
Multiagent Technology
33%
Genetic Algorithm
33%
Action Recognition
33%
Individual Interest
33%
Control Method
33%
Retrieval Algorithm
33%
BP neural network model
33%
Intelligent Transportation System
33%
Crack Segmentation Network
33%
Autoencoder
33%
Multiagent Simulation
33%
Classification Process
33%
multi agent simulation
33%
System Dynamics
33%
Decision-Making
33%
time-delay
33%
Fading Channel
33%
Engineering
Experimental Result
100%
Fault Diagnosis
66%
Genetic Algorithm
66%
Nash Equilibrium
50%
Simulation Result
44%
Realization
44%
Feature Extraction
33%
Energy Detection
33%
Based Expert System
33%
Detection Algorithm
33%
Maneuverability
33%
Parameter Uncertainty
33%
Classification Algorithm
33%
Discriminator
33%
Successive Frame
33%
Intelligent Transportation System
33%
Extraction Process
33%
Cognitive Network
33%
Image Enhancement
33%
Hardware System
33%
Current Frame
33%
Game Theory Model
33%
Research Issue
33%
Fading Channel
33%
Feature Vector
33%
Simulation System
33%
C4ISR System
33%
Peak Signal
33%
Multistage
33%
Threshold Energy
33%
Classification Process
33%
Autoencoder
33%
Recognition Rate
33%
Support Vector Machine
33%
Fault Management
33%
Face Image
33%
Big Difference
33%
Cooperative
33%
Adjacent Frame
33%
Histogram
33%
Edge Extraction
33%
Suspension System
33%
Active Suspension
33%
Control Algorithm
33%
Delay Time
27%
Obtains
25%
Ride Comfort
22%
Vehicle Suspensions
22%
Road Network
22%
Cognitive Receiver
16%
