Engineering
Manufacturing Company
100%
Additional Cost
100%
Data Series
100%
Production Line
100%
Anomaly Detection
100%
Learning Approach
100%
Condition Monitoring
100%
Convolutional Neural Network
100%
Automated Optical Inspection
100%
Convolutional Neural Network
100%
Dynamic Nature
50%
Illumination Condition
50%
Computervision
50%
Histogram
50%
Autoencoder
50%
Production Environment
50%
Light Condition
50%
Limited Number
50%
Detection Algorithm
50%
Quality Control
50%
Error Rate
33%
High Volume Production
33%
Negative Consequence
33%
Robot
33%
Human Operator
33%
Inspection Technology
33%
Visual Inspection
33%
Process Control
33%
High Quality Product
33%
Industrial Machinery
25%
Execution Time
25%
Digital Input
25%
Digital Output
25%
Industrial Equipment
25%
Support Vector Machine
25%
Input Signal
25%
Smart Manufacturing
25%
Recognition Rate
25%
Computer Science
Data Management
100%
Manufacturing Data
100%
Condition Monitoring
100%
Machine Learning
100%
Machine Learning Approach
100%
Anomaly Detection
100%
Convolutional Neural Network
100%
Production Line
100%
Training Data
100%
Autoencoder
50%
Dynamic Nature
50%
Computer Vision
50%
Production Environment
50%
Detection Algorithm
50%
Illumination Condition
50%
K-Means Clustering
50%
Varying Illumination
50%
Support Vector Machine
25%
Optimal Performance
25%
Execution Time
25%
Evaluation Measure
25%
Learning System
25%
Computational Efficiency
25%
Automated Machine Learning
25%
Product Quality
25%
Local Outlier Factor
25%
Machine Learning
25%
Hands-on Learning
16%
Collecting Data
16%
Digitalization
16%
Potential Benefit
16%
Initial Effort
16%
Machine Learning Technique
16%
