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Soldering Data Classification with a Deep Clustering Approach: Case Study of an Academic-Industrial...

Soldering Data Classification with a Deep Clustering Approach: Case Study of an Academic-Industrial...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_25f7d87eba4840dbaedfe285bfbdd201

Soldering Data Classification with a Deep Clustering Approach: Case Study of an Academic-Industrial Cooperation

About this item

Full title

Soldering Data Classification with a Deep Clustering Approach: Case Study of an Academic-Industrial Cooperation

Publisher

Basel: MDPI AG

Journal title

Applied sciences, 2022-07, Vol.12 (14), p.6927

Language

English

Formats

Publication information

Publisher

Basel: MDPI AG

More information

Scope and Contents

Contents

Modern industries still commonly use traditional methods to visually inspect products, even though automation has many advantages over the skills of human labour. The automation of redundant tasks is one of the greatest successes of Artificial Intelligence (AI). It employs human annotation and finds possible relationships between features within a...

Alternative Titles

Full title

Soldering Data Classification with a Deep Clustering Approach: Case Study of an Academic-Industrial Cooperation

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_25f7d87eba4840dbaedfe285bfbdd201

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_25f7d87eba4840dbaedfe285bfbdd201

Other Identifiers

ISSN

2076-3417

E-ISSN

2076-3417

DOI

10.3390/app12146927

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