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In-Season Cotton Yield Prediction with Scale-Aware Convolutional Neural Network Models and Unmanned Aerial Vehicle RGB Imagery

Sensors (Basel, Switzerland), 2024-04, Vol.24 (8), p.2432

2024

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Monitoring cotton (Gossypium hirsutum L.) germination using ultrahigh-resolution UAS images

Precision agriculture, 2018-02, Vol.19 (1), p.161-177

2018

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Unmanned Aircraft System- (UAS-) Based High-Throughput Phenotyping (HTP) for Tomato Yield Estimation

Journal of sensors, 2021, Vol.2021 (1)

2021

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Evaluating unsupervised and supervised image classification methods for mapping cotton root rot

Precision agriculture, 2015-04, Vol.16 (2), p.201-215

2015

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Energycane growth dynamics and potential early harvest penalties along the Texas Gulf Coast

Biomass & bioenergy, 2018-06, Vol.113, p.1-14

2018

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Measurement of Cotton Canopy Temperature Using Radiometric Thermal Sensor Mounted on the Unmanned Aerial Vehicle (UAV)

Journal of sensors, 2020, Vol.2020 (2020), p.1-7

2020

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Cotton fiber quality is related to boll location and planting date

Agronomy journal, 2004, Vol.96 (1), p.42-47

2004

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Cotton growth modeling and assessment using unmanned aircraft system visual-band imagery

Journal of applied remote sensing, 2016-08, Vol.10 (3), p.36018

2016

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Recording within-cotton distribution of plant bug injury using plant mapping computer-based tools

Crop protection, 2018-10, Vol.112, p.220-226

2018

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Monitoring Cotton Root Rot Progression within a Growing Season Using Airborne Multispectral Imagery

The journal of cotton science, 2014-01, Vol.18 (1), p.85-93

2014

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cotton fiber property variability continuum from motes through seeds

Textile research journal, 1999-10, Vol.69 (10), p.754-759

1999

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Cotton Fiber Quality is Related to Boll Location and Planting Date

Agronomy journal, 2004-01, Vol.96 (1), p.42-47

2004

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Spatial and Temporal Distribution of Surface Water Content in a Large Agricultural Field

Proceedings of the Fourth International Conference on Precision Agriculture, 1999, p.19-30

1999

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The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems

Current opinion in biotechnology, 2021-08, Vol.70, p.15-22

2021

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Testing the Performance of LSTM and ARIMA Models for In-Season Forecasting of Canopy Cover (CC) in Cotton Crops

Remote sensing (Basel, Switzerland), 2024-06, Vol.16 (11), p.1906

2024

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Cotton yield prediction utilizing unmanned aerial vehicles (UAV) and Bayesian neural networks

Computers and electronics in agriculture, 2024-11, Vol.226, p.109415, Article 109415

2024

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Comparison of Canopy Shape and Vegetation Indices of Citrus Trees Derived from UAV Multispectral Images for Characterization of Citrus Greening Disease

Remote sensing (Basel, Switzerland), 2020-12, Vol.12 (24), p.4122

2020

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Comparison of Vegetation Indices Derived from UAV Data for Differentiation of Tillage Effects in Agriculture

Remote sensing (Basel, Switzerland), 2019-07, Vol.11 (13), p.1548

2019

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Automated Open Cotton Boll Detection for Yield Estimation Using Unmanned Aircraft Vehicle (UAV) Data

Remote sensing (Basel, Switzerland), 2018-12, Vol.10 (12), p.1895

2018

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Performance Evaluation of Parallel Structure from Motion (SfM) Processing with Public Cloud Computing and an On-Premise Cluster System for UAS Images in Agriculture

ISPRS international journal of geo-information, 2021-10, Vol.10 (10), p.677

2021

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Improving Irrigation Management of Cotton with Small Unmanned Aerial Vehicle (UAV) in Texas High Plains

Water (Basel), 2024-05, Vol.16 (9), p.1300

2024

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Crop height monitoring with digital imagery from Unmanned Aerial System (UAS)

Computers and electronics in agriculture, 2017-09, Vol.141, p.232-237

2017

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Allocation trade-offs dominate the response of tropical forest growth to seasonal and interannual drought

Ecology (Durham), 2014-08, Vol.95 (8), p.2192-2201

2014

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3D Characterization of Sorghum Panicles Using a 3D Point Cloud Derived from UAV Imagery

Remote sensing (Basel, Switzerland), 2021-01, Vol.13 (2), p.282

2021

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Plant Counting of Cotton from UAS Imagery Using Deep Learning-Based Object Detection Framework

Remote sensing (Basel, Switzerland), 2020-09, Vol.12 (18), p.2981

2020

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In-Season Cotton Yield Prediction with Scale-Aware Convolutional Neural Network Models and Unmanned Aerial Vehicle RGB Imagery

Monitoring cotton (Gossypium hirsutum L.) germination using ultrahigh-resolution UAS images

Unmanned Aircraft System- (UAS-) Based High-Throughput Phenotyping (HTP) for Tomato Yield Estimation

Evaluating unsupervised and supervised image classification methods for mapping cotton root rot

Energycane growth dynamics and potential early harvest penalties along the Texas Gulf Coast

Measurement of Cotton Canopy Temperature Using Radiometric Thermal Sensor Mounted on the Unmanned Aerial Vehicle (UAV)

Cotton fiber quality is related to boll location and planting date

Cotton growth modeling and assessment using unmanned aircraft system visual-band imagery

Recording within-cotton distribution of plant bug injury using plant mapping computer-based tools

Monitoring Cotton Root Rot Progression within a Growing Season Using Airborne Multispectral Imagery

cotton fiber property variability continuum from motes through seeds

Cotton Fiber Quality is Related to Boll Location and Planting Date

Spatial and Temporal Distribution of Surface Water Content in a Large Agricultural Field

The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems

Testing the Performance of LSTM and ARIMA Models for In-Season Forecasting of Canopy Cover (CC) in Cotton Crops

Cotton yield prediction utilizing unmanned aerial vehicles (UAV) and Bayesian neural networks

Comparison of Canopy Shape and Vegetation Indices of Citrus Trees Derived from UAV Multispectral Images for Characterization of Citrus Greening Disease

Comparison of Vegetation Indices Derived from UAV Data for Differentiation of Tillage Effects in Agriculture

Automated Open Cotton Boll Detection for Yield Estimation Using Unmanned Aircraft Vehicle (UAV) Data

Performance Evaluation of Parallel Structure from Motion (SfM) Processing with Public Cloud Computing and an On-Premise Cluster System for UAS Images in Agriculture

Improving Irrigation Management of Cotton with Small Unmanned Aerial Vehicle (UAV) in Texas High Plains

Crop height monitoring with digital imagery from Unmanned Aerial System (UAS)

Allocation trade-offs dominate the response of tropical forest growth to seasonal and interannual drought

3D Characterization of Sorghum Panicles Using a 3D Point Cloud Derived from UAV Imagery

Plant Counting of Cotton from UAS Imagery Using Deep Learning-Based Object Detection Framework

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