Convolutional Neural Network Based On-Line Defect Recognition in Additive Manufacturing Using Image Processing-Reference-Cited by-同舟云学术

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Convolutional Neural Network Based On-Line Defect Recognition in Additive Manufacturing Using Image Processing

Published:2023-12-12 Issue: Volume: Page:1-6
ISSN:
Container-title:2023 4th International Conference on Computation, Automation and Knowledge Management (ICCAKM)
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Author:

Varade Harshal P.¹,Bhangale Sonal C.²,Patare P. M.¹,Ghanghav Vaibhav³,Sharma Santosh Kumar⁴,William P.³

Affiliation:

1. Sanjivani College of Engineering, Savitribai Phule Pune University,Department of Mechanical Engineering,Pune,India

2. Savitribai Phule Pune University,Sanjivani College of Engineering,Department of Mechatronics Engineering,Pune,India

3. Savitribai Phule Pune University,Sanjivani College of Engineering,Department of Information Technology,Pune,India

4. Chhattrapati Shivaji Institue of Technology,Department of Mechanical Engineering,Durg,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10449490/10449491/10449655.pdf?arnumber=10449655

Reference15 articles.

1. F3001–14 Standard Specification for Additive Manufacturing Titanium-6 Aluminum-4 Vanadium ELI (Extra Low Interstitial) with Powder Bed Fusion. West Conshohocken, PA,2014

2. Investigation of the Electronic and Optical Properties of Nanostructured Glasses and Composites

3. Empirical Analysis of the Emerging Trends in the Photovoltaic Technologies of Condensed Matter Physics

4. Green Synthesis Methods of Nanostructures for Environmental and Biomedical Applications

5. Analysis of Silver Nanoparticles as Carriers of Drug Delivery System

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