A REVIEW OF CONVOLUTIONAL NEURAL NETWORK IN EMERGING TRENDS AND OPPORTUNITIES IN PRECISION AGRICULTURE

Amit Hasan Sadhin and Reshad Rayhan
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Amit Hasan Sadhin: Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia.
Reshad Rayhan: Faculty of electrical engineering, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia.

Acta Informatica Malaysia (AIM), 2023, vol. 7, issue 2, 67-73

Abstract: Agriculture has always been integral to life’s existence as it directly depends on food production. Precision farming has emerged due to soft computing and information technology development trends. Food security has become a significant issue over the last few decades. Convolutional Neural Networks familiarize new sensations in precision agriculture; based on this, researchers have introduced effective planning, organized cultivation, smart irrigation, faster production, and cost reduction to address the continuously increasing demand for food supplies and to improve environmental as well as food sustainability. This paper contains a systematic review of various Convolutional Neural Network techniques in terms of the inescapable usefulness of modern agriculture to support food production for the ever-growing population, as well as the CNN adaptability in various agricultural sectors.

Keywords: Precision Farming; Convolution Neural Network; ANN (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:zib:zbnaim:v:7:y:2023:i:2:p:67-73

DOI: 10.26480/aim.02.2023.67.73

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