A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Automated Blood Cell Detection and Counting via Deep Learning for Microfluidic Point-of-Care Medical Devices
[article]
2019
arXiv
pre-print
Automated in-vitro cell detection and counting have been a key theme for artificial and intelligent biological analysis such as biopsy, drug analysis and decease diagnosis. Along with the rapid development of microfluidics and lab-on-chip technologies, in-vitro live cell analysis has been one of the critical tasks for both research and industry communities. However, it is a great challenge to obtain and then predict the precise information of live cells from numerous microscopic videos and
arXiv:1909.05393v1
fatcat:y6u2yw7yhvh2vio3pulv5zcxry