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  4. Smart agriculture: Predictive height analysis for universal crop health classification
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Smart agriculture: Predictive height analysis for universal crop health classification

Journal
Contemporary Engineering Sciences
Date Issued
2023
Author(s)
Tsakiridis, Sotirios  
Papaioannou, Nikolaos  
Tsimpiris, Alkiviadis  
Varsamis, Dimitrios  
Papakonstantinou, Apostolos  
DOI
10.12988/ces.2023.93115
Abstract
The use of contemporary information and communication technol- ogy to maximize agricultural output while reducing labor costs is known as ”smart agriculture”. This term is becoming more and more prevalent. The primary challenge in the agricultural sector lies in the vastness of crops, coupled with varied topography and soil instability, making con- trol challenging. In this paper, a system for determining the average predicted height of healthy plants at a given growth stage is proposed and evaluated. Based on this height, we then classify agricultural plants as healthy or unhealthy. It’s important to note that our system works with any crop kind and growth stage.
Subjects

Unsupervised Learning...

UAV

Smart Agriculture

Clustering

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tsimpirisCES1-2023.pdf

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786.14 KB

Format

Adobe PDF

Checksum (MD5)

5be4b55abb9c24ae352cc3ea2f04cfc3

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