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Project deliverable . 2017
License: CC BY NC ND
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License: CC BY NC ND
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Talent: Video Demonstration (New Functionalities)

Authors: ITI;

Talent: Video Demonstration (New Functionalities)

Abstract

TALENT (Research in Machine Learning techniques applied for open issues within the Industrial Manufacturing sector) is a project funded by the Valencian Institute for Business Competitiveness (IVACE) and the European Union through the European Regional Development Fund (FEDER). The general objective of this project is to advance in the design, implementation and industrialization of contact-free and occlusions-free automated inspection systems, introducing Machine Learning techniques. This will enable companies of the Valencia Region to increase product quality guarantees and thus strengthen their market position. This document contains a summary of the achieved results after the execution of a project in the line of research of applying machine learning techniques to solve different challenges proposed in the industrial sector in order to assess quality of parts manufactured in production lines.

TALENT. Project funded by the Valencian Institute of Business Competitiveness (IVACE) and European Union through the European Regional Development Fund (ERDF), within the public grant program adressed to Technological Institutes of the Valencian Community for the development of non-economic R&D projects carried out in cooperation with companies during 2017 with 199.670,64€. File number: IMDEEA/2017/90

Keywords

industry, 2017, web app, video, demo, TALENT, machine learning, metrology, quality control, defect detention, 3D

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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