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.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς:	Rinky, Habiba Karim, Bhuiyan, Rakeya Rahim, Rahman, Humayra Tasnim
Άλλοι συγγραφείς:	Chakrabarty, Amitabha
Μορφή:	Thesis
Γλώσσα:	English
Έκδοση:	Brac University 2021
Θέματα:	Malaria Plasmodium falciparum Plasmodium vivax Plasmodium malaria Plasmodium ovale Deep learning
Διαθέσιμο Online:	http://hdl.handle.net/10361/14725

Παρόμοια τεκμήρια

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