Identification of Parasitized Single Cell from Normal Using Deep Learning Approach-Reference-Cited by-同舟云学术

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Identification of Parasitized Single Cell from Normal Using Deep Learning Approach

Published:2022-03-23 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Decision Aid Sciences and Applications (DASA)
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Author:

Calderon Von Cedrick M.¹,Sarmiento Jeffrey S.¹,Cunanan Christopher Franco²,May C. Ceribo Carla³,Belga Gemma D.⁴

Affiliation:

1. Batangas State University,Computer Engineering Program,Batangas City,Philippines

2. Bulacan State University,Computer Engineering Department,Bulacan,Philippines

3. Southern Luzon State University,Computer Engineering Department,Quezon,Philippines

4. University of the Philippines,College of Industrial Technology Technological,Department of Electronics,Manila,Philippines

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9764877/9764959/09765258.pdf?arnumber=9765258

Reference25 articles.

1. Leveraging Deep Learning Techniques for Malaria Parasite Detection Using Mobile Application

2. Deep Learning Based Automatic Malaria Parasite Detection from Blood Smear and Its Smartphone Based Application

3. Parasitized Cell Recognition Using AlexNet Pre-trained Model

4. Cell Images Parasitized or Uninfected;Kaggle Com,2021

5. YOLOv3: An Incremental Improvement;redmon;ArXiv,2018

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