Sathishkumar Samiappan

Assistant Research Professor

Mississippi State University

United States

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About

Dr. Sathishkumar Samiappan is an Assistant Research Professor at Mississippi State University, USA. His research areas include artificial intelligence applications in environmental remote sensing, digital twin technology in smart agriculture, and the use of drone technology for wildlife monitoring. He has contributed to significant publications addressing various aspects of remote sensing, agricultural yield prediction, and the use of machine learning in crop science.

Articles (17)

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2025

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2024

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2024

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2022

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2022

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2022

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2021

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2021

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2020

Collaborators (10)

Deepak Mishra

University of Georgia

UNITED STATES

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Jared Elmore

Research Assistant Professor

Clemson University

UNITED STATES

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Joby Prince Czarnecki

Associate Research Professor

Mississippi State University

UNITED STATES

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Kellie J. Walters

University of Tennessee

UNITED STATES

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Kambham Raja Reddy

Research Professor

Mississippi State University

UNITED STATES

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T. Casey Barickman

Assistant Professor

Cornell University

UNITED STATES

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Robert J. Moorhead

Mississippi State University

UNITED STATES

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Raju Bheemanahalli

Assistant Research Professor

Mississippi State University

UNITED STATES

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Nuwan Wijewardane

Assistant Professor

Mississippi State University

UNITED STATES

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Xin Zhang

Assistant Professor

Mississippi State University

UNITED STATES

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Sathishkumar Samiappan

Research Interests

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About

Articles (17)

Morpho-physiological, leaf hyperspectral, and nutritional responses of lettuce to salt stress

Artificial intelligence in environmental remote sensing: Progress, way forward and key considerations

Context-Aware Deep Learning Model for Yield Prediction in Potato Using Time-Series UAS Multispectral Data

Application of Digital Twin Technology in Smart Agriculture: A Bibliometric Review

Feature Extraction in 5G Wireless Systems: A Quantum Cat Swarm and Wavelet-Based Approach

Battle Royale Optimization for Optimal Band Selection in Predicting Soil Nutrients Using Visible and Near-Infrared Reflectance Spectroscopy and PLSR Algorithm

Are unmanned aerial vehicle-based hyperspectral imaging and machine learning advancing crop science?

Relief displacement of airborne objects

Wildlife monitoring with drones: A survey of end users

Aerial Wildlife Image Repository for animal monitoring with drones in the age of artificial intelligence

Effects of drought and heat stresses during reproductive stage on pollen germination, yield, and leaf reflectance properties in maize (Zea mays L.)

Hyperspectral Reflectance and Machine Learning Approaches for the Detection of Drought and Root–Knot Nematode Infestation in Cotton

Evidence-based land conservation framework using multi-criteria acceptability analysis: A geospatial tool for strategic land conservation in the Gulf coast of the United States

Airborne Hyperspectral Imagery for Band Selection Using Moth–Flame Metaheuristic Optimization

Improving Animal Monitoring Using Small Unmanned Aircraft Systems (sUAS) and Deep Learning Networks

Real-Time Automated Classification of Sky Conditions Using Deep Learning and Edge Computing

A modified Cuckoo Search algorithm based optimal band subset selection approach for hyperspectral image classification

Collaborators (10)

Deepak Mishra

Jared Elmore

Joby Prince Czarnecki

Kellie J. Walters

Kambham Raja Reddy

T. Casey Barickman

Robert J. Moorhead

Raju Bheemanahalli

Nuwan Wijewardane

Xin Zhang

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