Publikationer pr. år
Publikationer pr. år
Projektdetaljer
Beskrivelse
Product aesthetics is a main quality parameter to be assessed in Danish manufacturing. Today this is mainly done manually and often the decision lies with one specific individual.
This project first of all aims at a better understanding of this process across different products and companies. Secondly, the project aims at automating/digitalizing the process, with the twofold goal of saving labor and making aesthetic quality less subjective and more quantifiable.
Manufacturing Academy of Denmark (MADE) - MADE Digital - Work Package 9
https://www.made.dk/digital/sensor-technology-and-production-data/
This project first of all aims at a better understanding of this process across different products and companies. Secondly, the project aims at automating/digitalizing the process, with the twofold goal of saving labor and making aesthetic quality less subjective and more quantifiable.
Manufacturing Academy of Denmark (MADE) - MADE Digital - Work Package 9
https://www.made.dk/digital/sensor-technology-and-production-data/
| Kort titel | Aesthetic Quality Control |
|---|---|
| Status | Afsluttet |
| Effektiv start/slut dato | 01/03/2017 → 01/08/2020 |
Samarbejdspartnere
- Bang & Olufsen A/S
- LEGO Systems AS
- VOLA
- Danish Technological Institute
- JLI Vision
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Udforsk forskningsemnerne, som dette projekt berører. Disse etiketter er oprettet på grundlag af de underliggende bevillinger/legater. Sammen danner de et unikt fingerprint.
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Defect or Design? Leveraging the Angle of Opportunity for detecting Scratches on Brushed Aluminium Surfaces
Hansen, A. J., Moeslund, T. B. & Knoche, H., 20 jul. 2021, I: IEEE Access. 9, s. 99526-99538 13 s., 9468644.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
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Machine Vision for Aesthetic Quality Control of Reflective Surfaces
Hansen, A. J., Philipsen, M. P., Knoche, H. & Moeslund, T. B., 2021, Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021) . Hassanien, A. E., Haqiq, A., Tonellato, P. J., Bellatreche, L., Goundar, S., Azar, A. T., Sabir, E. & Bouzidi, D. (red.). Springer, Bind 1377. s. 389-401 13 s. (Advances in Intelligent Systems and Computing).Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review
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Fantastic plastic? An Image-based Test Method to Detect Aesthetic Defects in Batches Based on Reference Samples
Hansen, A. J., Knoche, H. & Moeslund, T. B., 1 sep. 2020, I: Polymer Testing. 89, 106585.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Fil2 Citationer (Scopus)171 Downloads (Pure)