Green AI-Driven Concept for the Development of Cost-Effective and Energy-Efficient Deep Learning Method: Application in the Detection of Eimeria Parasites as a Case Study

Suheda Semih Acmali; Yasin Ortakci; Huseyin Seker

doi:10.1002/aisy.202300644

Green AI-Driven Concept for the Development of Cost-Effective and Energy-Efficient Deep Learning Method: Application in the Detection of Eimeria Parasites as a Case Study

Suheda Semih Acmali^*
, Yasin Ortakci^*
, Huseyin Seker

^*Corresponding author for this work

Zonguldak Karaelmas University
Karabuk University

Research output: Contribution to journal › Article › peer-review

1 Citation (SciVal)

Original language	English
Journal	Advanced Intelligent Systems
DOIs	https://doi.org/10.1002/aisy.202300644
Publication status	Published (VoR) - 12 Jun 2024

Keywords

convolutional neural networks
Eimeria classification
energy efficiency
green artificial intelligence
pretrained models
weight pruning

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10.1002/aisy.202300644Licence: CC BY

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title = "Green AI-Driven Concept for the Development of Cost-Effective and Energy-Efficient Deep Learning Method: Application in the Detection of Eimeria Parasites as a Case Study",

keywords = "convolutional neural networks, Eimeria classification, energy efficiency, green artificial intelligence, pretrained models, weight pruning",

author = "Acmali, \{Suheda Semih\} and Yasin Ortakci and Huseyin Seker",

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doi = "10.1002/aisy.202300644",

language = "English",

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T1 - Green AI-Driven Concept for the Development of Cost-Effective and Energy-Efficient Deep Learning Method

T2 - Application in the Detection of Eimeria Parasites as a Case Study

AU - Acmali, Suheda Semih

AU - Ortakci, Yasin

AU - Seker, Huseyin

PY - 2024/6/12

Y1 - 2024/6/12

KW - convolutional neural networks

KW - Eimeria classification

KW - energy efficiency

KW - green artificial intelligence

KW - pretrained models

KW - weight pruning

UR - https://www.scopus.com/pages/publications/85195672533

UR - https://www.scopus.com/pages/publications/85195672533#tab=citedBy

UR - https://www.open-access.bcu.ac.uk/15589/

U2 - 10.1002/aisy.202300644

DO - 10.1002/aisy.202300644

M3 - Article

AN - SCOPUS:85195672533

SN - 2640-4567

JO - Advanced Intelligent Systems

JF - Advanced Intelligent Systems

ER -

Green AI-Driven Concept for the Development of Cost-Effective and Energy-Efficient Deep Learning Method: Application in the Detection of Eimeria Parasites as a Case Study

Keywords

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