Cengiz Koparan

Assistant Professor

University of Arkansas at Fayetteville

United States

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About

Dr. Cengiz Koparan is an Assistant Professor at the University of Arkansas at Fayetteville, USA. His research focuses on precision agriculture, particularly in the areas of UAV-based weed identification, machine vision for site-specific weed management, and the application of deep learning algorithms in agricultural settings. He has published several recent articles addressing the impact of glyphosate on common lambsquarters and advances in unmanned aerial vehicle technologies for crop monitoring and management.

Articles (15)

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2025

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UNITED STATES

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Billy Graham Ram

Assistant Professor

Southern Illinois University Carbondale

UNITED STATES

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Cengiz Koparan

Research Interests

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Articles (15)

Hyperspectral indicators and characterization of glyphosate-induced stress in common lambsquarters (Chenopodium album L.)

A practical guide to UAV-based weed identification in soybean: Comparing RGB and multispectral sensor performance

Development and evaluation of a machine vision and deep learning-based smart sprayer system for site-specific weed management in row crops: An edge computing approach

Blackberry Growth Monitoring and Feature Quantification with Unmanned Aerial Vehicle (UAV) Remote Sensing

Inservice needs of selected Arkansas agriculture teachers related to precision agriculture

Advances in ground robotic technologies for site-specific weed management in precision agriculture: A review

A REVIEW OF THE CURRENT UNMANNED AERIAL VEHICLE SPRAYER APPLICATIONS IN PRECISION AGRICULTURE

A study on deep learning algorithm performance on weed and crop species identification under different image background

Multiclass Classification on Soybean and Weed Species Using a Customized Greenhouse Robotic and Hyperspectral Combination System

Weed and crop species classification using computer vision and deep learning technologies in greenhouse conditions

Image based thermal sensing for glyphosate resistant weed identification in greenhouse conditions

A Technical Study on UAV Characteristics for Precision Agriculture Applications and Associated Practical Challenges

UAV-Assisted Thermal Infrared and Multispectral Imaging of Weed Canopies for Glyphosate Resistance Detection

Temperature Profiling of Waterbodies with a UAV-Integrated Sensor Subsystem

Adaptive Water Sampling Device for Aerial Robots

Collaborators (8)

Nilda Roma-Burgos

Dongyi Wang

Donald Johnson

Calvin Sawyer

Igathinathane Cannayen

Aurelie Poncet

Kristofor R. Brye

Billy Graham Ram

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