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A deep learning-based automated Solar-Powered Fish Monitoring System · Peerford

Article · Journal · 2026

A deep learning-based automated Solar-Powered Fish Monitoring System

Emmanuel Ahene, Richmond Owusu Agyei, Rose-Mary Owusuaa Mensah Gyening, Kwasi Adu Obirikorang, Kate Takyi, Kwabena Owusu-Agyemang and 2 more

PLoS ONE

Open access · Gold
International · 2 countries

Read it 10.1371/journal.pone.0351628

Citations: 0from other works
Field-weighted impact: 0.001.00 is the world average for its field and year
Among its field: 41st percentileby citations, against works of its field and year
Authors: 8from 2 institutions

Authors

8 authors across 2 institutions in 2 countries

Emmanuel AheneFirst authorCorresponding
- Kwame Nkrumah University of Science and Technology (GH)
Richmond Owusu Agyei
- Kwame Nkrumah University of Science and Technology (GH)
Rose-Mary Owusuaa Mensah Gyening
- Kwame Nkrumah University of Science and Technology (GH)
Kwasi Adu Obirikorang
- Kwame Nkrumah University of Science and Technology (GH)
Kate Takyi
- Kwame Nkrumah University of Science and Technology (GH)

Kwabena Owusu-Agyemang

Kwame Nkrumah University of Science and Technology (GH)

Linda Amoako Banning

Kwame Nkrumah University of Science and Technology (GH)

as printed: Linda Amoako-Banning

Joojo WalkerSenior author

Development goals

12Responsible consumption and production

Funded by

Kwame Nkrumah University of Science and Technology

Countries on it

China
Ghana

Also on it

Chengdu University of Technologyeducation · CN

Fields

A work can sit in several, each with a score

Water Quality Monitoring TechnologiesTopic
Innovations in Aquaponics and Hydroponics SystemsTopic
Aquaculture Nutrition and GrowthTopic