Convolutional Neural Network Detection and Classification of Blood Cell Images from Thin Blood Smear for the Presence of Malarial Parasite
Author:
Affiliation:
1. VIT Bhopal University,School of Computing Science and Engineering,Bhopal,India
2. Presidency University,School of Information Science,Bangalore,Karnataka,560064
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10525677/10525695/10525750.pdf?arnumber=10525750
Reference18 articles.
1. Automated Enumeration of Malaria Parasite Using SVM Classifier;Sayali;International Journal for Research Trends and Innovation
2. DeepFMD: Computational Analysis for Malaria Detection in Blood-Smear Images Using Deep-Learning Features
3. Leveraging Deep Learning Techniques for Malaria Parasite Detection Using Mobile Application
4. Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images
5. DeepFMD: Computational Analysis for Malaria Detection in Blood-Smear Images Using Deep-Learning Features;Abubakar;MDPI,2022
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