A Novel Data Augmentation Convolutional Neural Network for Detecting Malaria Parasite in Blood Smear Images-Reference-Cited by-同舟云学术

A Novel Data Augmentation Convolutional Neural Network for Detecting Malaria Parasite in Blood Smear Images

Published:2022-01-25 Issue:1 Volume:36 Page:
ISSN:0883-9514
Container-title:Applied Artificial Intelligence
language:en
Short-container-title:Applied Artificial Intelligence

Author:

Oyewola David Opeoluwa¹^ORCID,Dada Emmanuel Gbenga²^ORCID,Misra Sanjay³^ORCID,Damaševičius Robertas⁴^ORCID

Affiliation:

1. Department of Mathematics and Computer Science, Federal University Kashere, Gombe, Nigeria

2. Department of Mathematical Sciences, University of Maiduguri, Maiduguri, Nigeria

3. Department of Computer Science and Communication, Østfold University College, Halden, Norway

4. Faculty of Applied Mathematics, Silesian University of Technology, Gliwice, Poland

Publisher

Informa UK Limited

Subject

Artificial Intelligence

Link

https://www.tandfonline.com/doi/pdf/10.1080/08839514.2022.2033473

Reference53 articles.

1. The impact of artificial intelligence in medicine on the future role of the physician

2. Deep Learning‐Based Image Classifier for Malaria Cell Detection

3. A State-of-the-Art Survey on Deep Learning Theory and Architectures

4. Malaria Parasite Detection From Peripheral Blood Smear Images Using Deep Belief Networks

5. Bjorck, N., C. P. Gomes, B. Selman, and K. Q. Weinberger. 2018. Understanding batch normalization. 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), Montréal, Canada.

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