AI-Enabled Quality Control: Detecting Defects in Manufacturing Processes with Convolutional Neural Networks

This paper aims to establish an improvement upon previous approaches to defect detection, namely, the CNN model and how it is more effective than edge detection and histogram-based methods for manufacturing defects. Overall, the model that used a set of 10,000 images as the training basis presented...

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Veröffentlicht in:	International Conference on Computing, Communication and Automation (Online) S. 1 - 6
Hauptverfasser:	S.Rajarajeswari, Prasadarao, J, Adnan, Myasar Mundher, Kaur, Simranjit, Vishwakarma, Ravi, Vinoth, R.
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 22.11.2024
Schlagworte:	Accuracy Chipper Text Policy-Attribute Based Encryption Algorithm Cloud Computing Computational modeling Convolutional neural networks Defect detection Encryption Encryption Time Image edge detection Manufacturing Manufacturing processes Multilevel authentication Novel Lightweight Cryptography Method Technology Quality assurance Transfer learning
ISSN:	2642-7354
Online-Zugang:	Volltext
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