Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/31228
Title: | Multi-frequency electrical impedance analysis for monitoring aqueous solutions using an accelerated neural network approach | Authors: | LEMMENS, Marijn De Raedt, W GRIETEN, Lars THOELEN, Ronald |
Issue Date: | 2019 | Source: | Engineering of Functional Interfaces (EnFi 2019), Leuven, Belgium, 8 - 9 July 2019 | 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 | Document URI: | http://hdl.handle.net/1942/31228 | Category: | C2 | Type: | Conference Material |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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poster.pdf Restricted Access | Conference material | 2.43 MB | Adobe PDF | View/Open Request a copy |
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