Performance comparison of CNN architectures for detecting Malaria diseases

Performance comparison of CNN architectures for detecting Malaria diseases

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.

Bibliografski detalji
Glavni autori:	Rinky, Habiba Karim, Bhuiyan, Rakeya Rahim, Rahman, Humayra Tasnim
Daljnji autori:	Chakrabarty, Amitabha
Format:	Disertacija
Jezik:	English
Izdano:	Brac University 2021
Teme:	Malaria Plasmodium falciparum Plasmodium vivax Plasmodium malaria Plasmodium ovale Deep learning
Online pristup:	http://hdl.handle.net/10361/14725

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