Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/31228
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | LEMMENS, Marijn | - |
dc.contributor.author | De Raedt, W | - |
dc.contributor.author | GRIETEN, Lars | - |
dc.contributor.author | THOELEN, Ronald | - |
dc.date.accessioned | 2020-05-27T08:53:42Z | - |
dc.date.available | 2020-05-27T08:53:42Z | - |
dc.date.issued | 2019 | - |
dc.date.submitted | 2020-04-20T19:23:26Z | - |
dc.identifier.citation | Engineering of Functional Interfaces (EnFi 2019), Leuven, Belgium, 8 - 9 July 2019 | - |
dc.identifier.uri | http://hdl.handle.net/1942/31228 | - |
dc.description.abstract | At this very moment we find ourselves in the age of sensor technology, every device has an uplink to some kind of cloud-platform which will in return make the devices smart. When talking about smart devices the term Artificial Intelligence comes very quickly to mind. In this proofof-concept study a neural network is made to distinguish the throughput of fluids in real-time Having this amount of information at your disposal, processing it becomes a major challenge. However, when looking into the artificial intelligence research branch, techniques can be derived to process this data resulting into a more compact form factor of the same data with the benefit of using this derived data to classify, or even predict reoccurring patterns | - |
dc.description.sponsorship | This work is funded by the BIOMAT project which is carried out under Interreg V-A grensregio Vlaanderen - Nederland and is supported by the European Union and The European Regional Development Fund and with financial support of province of Limburg - Belgium. | - |
dc.language.iso | en | - |
dc.title | Multi-frequency electrical impedance analysis for monitoring aqueous solutions using an accelerated neural network approach | - |
dc.type | Conference Material | - |
local.bibliographicCitation.conferencedate | 8 - 9 July 2019 | - |
local.bibliographicCitation.conferencename | Engineering of Functional Interfaces (EnFi 2019) | - |
local.bibliographicCitation.conferenceplace | Leuven, Belgium | - |
local.format.pages | 1 | - |
local.bibliographicCitation.jcat | C2 | - |
local.type.refereed | Refereed | - |
local.type.specified | Conference Poster | - |
local.provider.type | - | |
local.uhasselt.uhpub | yes | - |
item.contributor | LEMMENS, Marijn | - |
item.contributor | De Raedt, W | - |
item.contributor | GRIETEN, Lars | - |
item.contributor | THOELEN, Ronald | - |
item.fullcitation | LEMMENS, Marijn; De Raedt, W; GRIETEN, Lars & THOELEN, Ronald (2019) Multi-frequency electrical impedance analysis for monitoring aqueous solutions using an accelerated neural network approach. In: Engineering of Functional Interfaces (EnFi 2019), Leuven, Belgium, 8 - 9 July 2019. | - |
item.accessRights | Restricted Access | - |
item.fulltext | With Fulltext | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
poster.pdf Restricted Access | Conference material | 2.43 MB | Adobe PDF | View/Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.