Accurate Sickle Cell Detection Using Deep Transfer Learning Based Feature Extraction, Classification, and Retrieval of Blood Smear Images

Text Registration

Accurate Sickle Cell Detection Using Deep Transfer Learning Based Feature Extraction, Classification, and Retrieval of Blood Smear Images

Status

Published

on 18 Jun 2021

Year of Creation

2021

Victor T. Opadeji

Registration Number

TX0008990974

on 18 Jun 2021

The U.S. Copyright record (Registration Number: TX0008990974) dated 18 Jun 2021, pertains to an electronic file (eService) titled "Accurate Sickle Cell Detection Using Deep Transfer Learning Based Feature Extraction, Classification, and Retrieval of Blood Smear Images" created in 2021. The copyright holder is Victor T. Opadeji, known for their creative contributions in text registration. For any inquiries concerning this copyrighted material, kindly reach out to Victor T. Opadeji.

Victor T. Opadeji

Application Details

Registration Number

TX0008990974

Registration Date

6/18/2021

Year of Creation

2021

Agency Marc Code

DLC-CO

Record Status

New

Physical Description

Electronic file (eService)

First Publication Nation

United States

Personal Authors

Opadeji Victor Toluwanimi

Notes

Rights Note: Mark Dill, ProQuest, LLC, 789 E. Eisenhower Parkway, Ann Arbor, MI, 48108-3218, United States, (800) 521-0600, disspub@proquest.com

Statements

Application Title Statement: Accurate Sickle Cell Detection Using Deep Transfer Learning Based Feature Extraction, Classification, and Retrieval of Blood Smear Images

Author Statement: Opadeji Victor Toluwanimi Citizenship: not known Authorship: text

Notes

Rights Note: Mark Dill, ProQuest, LLC, 789 E. Eisenhower Parkway, Ann Arbor, MI, 48108-3218, United States, (800) 521-0600, disspub@proquest.com

Statements

Application Title Statement: Accurate Sickle Cell Detection Using Deep Transfer Learning Based Feature Extraction, Classification, and Retrieval of Blood Smear Images

Author Statement: Opadeji Victor Toluwanimi Citizenship: not known Authorship: text

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