Naslov: | A review of federated learning in agriculture |
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Avtorji: | ID Rizman Žalik, Krista (Avtor) ID Žalik, Mitja (Avtor) |
Datoteke: | sensors-23-09566.pdf (839,33 KB) MD5: 27F3FBAC5BD6C26959AC1CCE3B21B98F
https://www.mdpi.com/1424-8220/23/23/9566
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Jezik: | Angleški jezik |
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Vrsta gradiva: | Članek v reviji |
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Tipologija: | 1.02 - Pregledni znanstveni članek |
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Organizacija: | FNM - Fakulteta za naravoslovje in matematiko FERI - Fakulteta za elektrotehniko, računalništvo in informatiko
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Opis: | Federated learning (FL), with the aim of training machine learning models using data and computational resources on edge devices without sharing raw local data, is essential for improving agricultural management and smart agriculture. This study is a review of FL applications that address various agricultural problems. We compare the types of data partitioning and types of FL (horizontal partitioning and horizontal FL, vertical partitioning and vertical FL, and hybrid partitioning and transfer FL), architectures (centralized and decentralized), levels of federation (cross-device and cross-silo), and the use of aggregation algorithms in different reviewed approaches and applications of FL in agriculture. We also briefly review how the communication challenge is solved by different approaches. This work is useful for gaining an overview of the FL techniques used in agriculture and the progress made in this field. |
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Ključne besede: | federated learning, agriculture, architecture, data partitioning, federation scal, aggregation algorithms, communication bottleneck |
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Status publikacije: | Objavljeno |
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Verzija publikacije: | Objavljena publikacija |
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Poslano v recenzijo: | 11.10.2023 |
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Datum sprejetja članka: | 29.11.2023 |
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Datum objave: | 02.12.2023 |
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Založnik: | MDPI |
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Leto izida: | 2023 |
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Št. strani: | 20 str. |
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Številčenje: | Vol. 23, iss. 23, [article no.] 9566 |
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PID: | 20.500.12556/DKUM-88287  |
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UDK: | 004.8 |
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COBISS.SI-ID: | 179436547  |
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DOI: | 10.3390/s23239566  |
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ISSN pri članku: | 1424-8220 |
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Avtorske pravice: | © 2023 by the authors |
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Datum objave v DKUM: | 05.06.2024 |
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Število ogledov: | 142 |
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Število prenosov: | 37 |
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Metapodatki: |  |
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Področja: | Ostalo
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