A microfluidic microalgae detection system for cellular physiological response based on an object detection algorithm-Reference-Cited by-同舟云学术

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A microfluidic microalgae detection system for cellular physiological response based on an object detection algorithm

Published:2024 Issue:10 Volume:24 Page:2762-2773
ISSN:1473-0197
Container-title:Lab on a Chip
language:en
Short-container-title:Lab Chip

Author:

Zhou Shizheng¹²,Chen Tianhui¹,Fu Edgar S.³,Zhou Teng⁴,Shi Liuyong⁴,Yan Hong¹²^ORCID

Affiliation:

1. School of Computer Science and Technology, Hainan University, Haikou 570228, China

2. State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou 570228, China

3. Graduate School of Computing and Information Science, University of Pittsburgh, PA 15260, USA

4. School of Mechanical and Electrical Engineering, Hainan University, Haikou 570228, China

Abstract

We present a label-free, multi-scale, sheath-less microfluidic microalgae detection system enabled with an improved deep learning algorithm, called MD-YOLO, for tiny cell classification and physiological status monitoring.

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/LC/D3LC00941F

Reference45 articles.

1. Algae biotechnology for industrial wastewater treatment, bioenergy production, and high-value bioproducts

2. Microalgae based production of single-cell protein

3. Global market and economic analysis of microalgae technology: Status and perspectives

4. A review on co-culturing of microalgae: A greener strategy towards sustainable biofuels production

5. Airborne microalgal and cyanobacterial diversity and composition during rain events in the southern Baltic Sea region

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