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.

Dades bibliogràfiques
Autors principals:	Rinky, Habiba Karim, Bhuiyan, Rakeya Rahim, Rahman, Humayra Tasnim
Altres autors:	Chakrabarty, Amitabha
Format:	Thesis
Idioma:	English
Publicat:	Brac University 2021
Matèries:	Malaria Plasmodium falciparum Plasmodium vivax Plasmodium malaria Plasmodium ovale Deep learning
Accés en línia:	http://hdl.handle.net/10361/14725

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