INIS
pipelines
92%
filters
67%
assessments
67%
detection
56%
underwater
51%
underwater vehicles
46%
learning
42%
data
42%
images
41%
fluxgate magnetometers
35%
surveys
35%
hypothesis
30%
safety
30%
density
30%
probability
30%
inspection
30%
reliability
30%
machine learning
30%
pipes
28%
sensors
25%
algorithms
25%
simulation
25%
tracks
21%
Engineering
Autonomous Underwater Vehicle
100%
Real Data
46%
Joints (Structural Components)
30%
Reliability Assessment
30%
Safety Argument
30%
Operational Cost
30%
Buried Pipelines
30%
Edge Detection
30%
Computer Science
Challenging Scenario
30%
Detection Pipeline
30%
Network Segmentation
30%
Machine Learning
30%
Trained Network
30%
System Assurance
30%
Learning Component
30%
Operational Cost
30%
Large Data Set
30%
Deep Neural Network
30%
