A Comprehensive Approach Toward Wheat Leaf Disease Identification Leveraging Transformer Models and Federated Learning-Reference-Cited by-同舟云学术

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A Comprehensive Approach Toward Wheat Leaf Disease Identification Leveraging Transformer Models and Federated Learning

Published:2024 Issue: Volume:12 Page:109128-109156
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Fahim-Ul-Islam Md.¹^ORCID,Chakrabarty Amitabha¹^ORCID,Ahmed Sarder Tanvir¹,Rahman Rafeed¹,Kwon Hyun Han²^ORCID,Jalil Piran Md.³^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Brac University, Dhaka, Bangladesh

2. Department of Civil and Environmental Engineering, Sejong University, Seoul, South Korea

3. Department of Computer Science and Engineering, Sejong University, Seoul, South Korea

Funder

Korea Environmental Industry and Technology Institute (KEITI) through the Water Management Program for Drought Project, funded by Korea Ministry of Environment

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10623136.pdf?arnumber=10623136

Reference48 articles.

1. Genome-wide association study identifies novel loci and candidate genes for rust resistance in wheat (Triticum aestivum L.)

2. Conflict in Ukraine and the unsettling ripples: implications on food systems and development in North Africa

3. Challenges and technological interventions in rice–wheat system for resilient food–water–energy-environment nexus in North-western Indo-Gangetic Plains: A review

4. Enhancing traceability of wheat quality through the supply chain

5. Fungal wheat diseases: Etiology, breeding, and integrated management, volume II

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