A robust recognition error recovery for micro-flow cytometer by machine-learning enhanced single-frame super-resolution processing
With the recent advancement in microfluidics based lab-on-a-chip technology, lensless imaging system integrating microfluidic channel with CMOS image sensor has become a promising solution for the system minimization of flow cytometer. The design challenge for such an imaging-based micro-flow cytome...
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Main Authors: | , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2014
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/79256 http://hdl.handle.net/10220/24495 |
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Institution: | Nanyang Technological University |
Language: | English |
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