Cassava disease recognition from low‐quality images using enhanced data augmentation model and deep learning-Reference-Cited by-同舟云学术

Cassava disease recognition from low‐quality images using enhanced data augmentation model and deep learning

Published:2021-06-14 Issue:7 Volume:38 Page:
ISSN:0266-4720
Container-title:Expert Systems
language:en
Short-container-title:Expert Systems

Author:

Abayomi‐Alli Olusola Oluwakemi¹,Damaševičius Robertas¹,Misra Sanjay²³^ORCID,Maskeliūnas Rytis⁴⁵

Affiliation:

1. Department of Software Engineering Kaunas University of Technology Kaunas Lithuania

2. Department of Computer Engineering Atilim University Ankara Turkey

3. Department of Electrical and Information Engineering Covenant University Ota Nigeria

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

5. Department of Applied Informatics Vytautas Magnus University Kaunas Lithuania

Publisher

Wiley

Subject

Artificial Intelligence,Computational Theory and Mathematics,Theoretical Computer Science,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.12746

Reference89 articles.

1. Abayomi‐Alli O. O. Damasevicius R. Maskeliunas R. &Abayomi‐Alli A.(2020).BiLSTM with data augmentation using interpolation methods to improve early detection of parkinson disease. In 2020 federated conference on computer science and information systems FedCSIS 2020 Sofia Bulgaria (pp. 371–380).

2. Abayomi‐Alli O. O. Damaševičius R. Wieczorek M. &Woźniak M.(2020).Data augmentation using principal component resampling for image recognition by deep learning. In 19th international conference on artificial intelligence and soft computing ICAISC 2020 Zakopane Poland LNAI 12416 (pp. 39–48).

3. A machine learning model for field diagnosis of cassava mosaic disease;Aduwo J. R.;International Journal of Computer and Information (IJCIT),2019

4. Afrimash. (2016).Economic importance of cassava production in Nigeria. Retrieved fromhttps://www.afrimash.com/economic-importance-of-cassava-production-in-nigeria/

5. Economic impacts of cassava research and extension in Malawi and Zambia. Journal development;Alene D.;Agriculture. Economics,2013

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