Analysis of Formal Concepts for Verification of Pests and Diseases of Crops Using Machine Learning Methods-Reference-Cited by-同舟云学术

Analysis of Formal Concepts for Verification of Pests and Diseases of Crops Using Machine Learning Methods

Published:2024 Issue: Volume:12 Page:19902-19910
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Tussupov Jamalbek¹^ORCID,Yessenova Moldir¹^ORCID,Abdikerimova Gulzira¹,Aimbetov Aidyn²,Baktybekov Kazbek³^ORCID,Murzabekova Gulden⁴^ORCID,Aitimova Ulzada⁴^ORCID

Affiliation:

1. L. N. Gumilyov Eurasian National University, Astana, Kazakhstan

2. JSC National Company Kazakhstan Garysh Sapary, Astana, Kazakhstan

3. Kazakh-French Space Enterprise Galam LLP, Astana, Kazakhstan

4. S. Seifullin Kazakh Agro Technical Research University, Astana, Kazakhstan

Funder

Science Committee of the Ministry of Science and Higher Education, Kazakhstan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10418240.pdf?arnumber=10418240

Reference37 articles.

1. Identification of factors that negatively affect the growth of agricultural crops by methods of orthogonal transformations

2. The applicability of informative textural features for the detection of factors negatively influencing the growth of wheat on aerial images

3. The effectiveness of methods and algorithms for detecting and isolating factors that negatively affect the growth of crops

4. Features of growth of agricultural crops and factors negatively affecting their growth

5. Extended Vision Transformer (ExViT) for Land Use and Land Cover Classification: A Multimodal Deep Learning Framework

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