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

J Jung, M Maeda, A Chang, M Bhandari… - Current Opinion in …, 2021 - Elsevier
Modern agriculture and food production systems are facing increasing pressures from
climate change, land and water availability, and, more recently, a pandemic. These factors …

Internet of things (IoT) and agricultural unmanned aerial vehicles (UAVs) in smart farming: A comprehensive review

AD Boursianis, MS Papadopoulou, P Diamantoulakis… - Internet of Things, 2022 - Elsevier
Abstract Internet of Things (IoT) and Unmanned Aerial Vehicles (UAVs) are two hot
technologies utilized in cultivation fields, which transform traditional farming practices into a …

A review on UAV-based applications for precision agriculture

DC Tsouros, S Bibi, PG Sarigiannidis - Information, 2019 - mdpi.com
Emerging technologies such as Internet of Things (IoT) can provide significant potential in
Smart Farming and Precision Agriculture applications, enabling the acquisition of real-time …

Developing a machine learning based cotton yield estimation framework using multi-temporal UAS data

A Ashapure, J Jung, A Chang, S Oh, J Yeom… - ISPRS Journal of …, 2020 - Elsevier
In this research a machine learning framework was developed for cotton yield estimation
using multi-temporal remote sensing data collected from unmanned aircraft system (UAS) …

Classification of soybean leaf wilting due to drought stress using UAV-based imagery

J Zhou, J Zhou, H Ye, ML Ali, HT Nguyen… - … and Electronics in …, 2020 - Elsevier
Drought stress is one of the major limiting factors in soybean growth and productivity.
Canopy leaf wilting (ie fast-and slow-wilting) is considered as an important visible symptom …

Plant counting of cotton from UAS imagery using deep learning-based object detection framework

S Oh, A Chang, A Ashapure, J Jung, N Dube… - Remote Sensing, 2020 - mdpi.com
Assessing plant population of cotton is important to make replanting decisions in low plant
density areas, prone to yielding penalties. Since the measurement of plant population in the …

[HTML][HTML] Downscaling solar-induced chlorophyll fluorescence for field-scale cotton yield estimation by a two-step convolutional neural network

X Kang, C Huang, L Zhang, Z Zhang, X Lv - Computers and Electronics in …, 2022 - Elsevier
As the largest cotton-growing region in China, Xinjiang has contributed more than 80% of
the total national cotton production in recent years. Timely and accurate estimation of cotton …

Data acquisition and analysis methods in UAV-based applications for Precision Agriculture

DC Tsouros, A Triantafyllou, S Bibi… - … Computing in Sensor …, 2019 - ieeexplore.ieee.org
Emerging technologies such as Internet of Things (IoT) can provide significant potential in
Precision Agriculture enabling the acquisition of real-time environmental data. IoT devices …

A support vector machine and image processing based approach for counting open cotton bolls and estimating lint yield from UAV imagery

A Bawa, S Samanta, SK Himanshu, J Singh… - Smart Agricultural …, 2023 - Elsevier
Cotton boll count is an important phenotypic trait that aids in a better understanding of the
genetic and physiological mechanisms of cotton growth. Several computer vision …

Unmanned aerial vehicle-based phenotyping using morphometric and spectral analysis can quantify responses of wild tomato plants to salinity stress

K Johansen, MJL Morton, YM Malbeteau… - Frontiers in Plant …, 2019 - frontiersin.org
With salt stress presenting a major threat to global food production, attention has turned to
the identification and breeding of crop cultivars with improved salt tolerance. For instance …