A Deep Learning-based Microsection Measurement Framework for Print Circuit Boards

Keyphrases

• Adaptation 50%
• Analysis Operator 25%
• Convolutional Neural Network Model 25%
• Cross-section Analysis 25%
• Deep Learning Methods 100%
• Destructive Testing 25%
• Detection Module 50%
• Effective Alternative 25%
• Image Processing 50%
• Inconsistency 25%
• Manual Measurement 25%
• Measurement Accuracy 25%
• Measurement Framework 100%
• Measurement Method 25%
• Microdissection 100%
• Operator Measure 25%
• Preprocessing Module 50%
• Printed Circuit Board 100%
• Punctuation 25%
• Readability 25%
• Root Mean Square Error 25%
• Size Dependence 25%
• Standardized Procedure 25%
• Straight Line 25%
• Target Detection 50%
• Testing Procedures 25%

Computer Science

• Convolutional Neural Network 33%
• Deep Learning Method 100%
• Experimental Result 33%
• Manual Measurement 33%
• Measurement Framework 100%
• Measurement Method 33%
• Neural Network Model 33%
• Preprocessing Module 66%
• Printed Circuit Board 100%
• Testing Procedure 33%

Engineering

• Convolutional Neural Network 33%
• Cross-Section Analysis 33%
• Deep Learning Method 100%
• Destructive Testing 33%
• Experimental Result 33%
• Manual Measurement 33%
• Network Model 33%
• Printed Circuit Board 100%
• Root Mean Square Error 33%
• Straight Line 33%
• Target Area 33%
• Target Tracking 66%