Engineering
Convolutional Neural Network
100%
Manufacturing Company
45%
Additional Cost
45%
Data Series
45%
Production Line
45%
Anomaly Detection
45%
Learning Approach
45%
Condition Monitoring
45%
Automated Optical Inspection
45%
Learning System
45%
Artificial Intelligence
45%
Luminous Intensity
45%
Long Short-Term Memory Network
27%
Long Short-Term Memory
27%
Dynamic Nature
22%
Illumination Condition
22%
Computervision
22%
Histogram
22%
Autoencoder
22%
Production Environment
22%
Light Condition
22%
Limited Number
22%
Detection Algorithm
22%
Quality Control
22%
Industrial Robot
22%
Error Rate
15%
High Volume Production
15%
Negative Consequence
15%
Robot
15%
Human Operator
15%
Inspection Technology
15%
Visual Inspection
15%
Process Control
15%
High Quality Product
15%
Industrial Machinery
11%
Execution Time
11%
Digital Input
11%
Digital Output
11%
Industrial Equipment
11%
Support Vector Machine
11%
Input Signal
11%
Smart Manufacturing
11%
Recognition Rate
11%
Artificial Neural Network
9%
Computer Science
Data Management
45%
Manufacturing Data
45%
Condition Monitoring
45%
Machine Learning Approach
45%
Anomaly Detection
45%
Luminous Intensity
45%
Enterprise Resource Planning System
45%
Inline Assembly
45%
Autoencoder
22%
YOLO
22%
Quality Control
22%
Computer Vision
22%
Supervised Learning
22%
Collected Data
22%
Throughput Time
22%
Fault Detection
22%
Industrial Robot
22%
Decision Tree
22%
Support Vector Machine
11%
Optimal Performance
11%
Execution Time
11%
Evaluation Measure
11%
Learning System
11%
Computational Efficiency
11%
Automated Machine Learning
11%
Product Quality
11%
Local Outlier Factor
11%
Machine Learning
11%
Hands-on Learning
7%
Collecting Data
7%
Digitalization
7%
Potential Benefit
7%
Initial Effort
7%
Machine Learning Technique
7%
