Unsupervised identification of malaria parasites using computer vision
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/6829975/6841829/06841878.pdf?arnumber=6841878
Cited by 28 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Utilizing Image Analysis with Machine Learning and Deep Learning to Identify Malaria Parasites in Conventional Microscopic Blood Smear Images;Traitement du Signal;2024-02-29
2. An Automatic Malaria Disease Diagnosis Framework Integrating Blockchain-Enabled Cloud–Edge Computing and Deep Learning;IEEE Internet of Things Journal;2023-12-15
3. A Transfer Learning Applied for Malaria Disease Detection on Blood Smear Images;2023 19th International Symposium on Medical Information Processing and Analysis (SIPAIM);2023-11-15
4. Recognition System for Malarial Parasites Causing Protozoa Infections in Thin Blood Smears;2023 IEEE 4th Annual Flagship India Council International Subsections Conference (INDISCON);2023-08-05
5. Edge-Based Segmentation for Accurate Detection of Malaria Parasites in Microscopic Blood Smear Images: A Novel Approach using FCM and MPP Algorithms;2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN);2023-04-21
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