A review of remote sensing applications in agriculture for food security: Crop growth and yield, irrigation, and crop losses
The global population is expected to reach 9.8 billion by 2050. There is an exponential
growth of food production to meet the needs of the growing population. However, the limited …
growth of food production to meet the needs of the growing population. However, the limited …
Implementation of machine-learning classification in remote sensing: An applied review
Machine learning offers the potential for effective and efficient classification of remotely
sensed imagery. The strengths of machine learning include the capacity to handle data of …
sensed imagery. The strengths of machine learning include the capacity to handle data of …
Quantifying vegetation biophysical variables from imaging spectroscopy data: A review on retrieval methods
An unprecedented spectroscopic data stream will soon become available with forthcoming
Earth-observing satellite missions equipped with imaging spectroradiometers. This data …
Earth-observing satellite missions equipped with imaging spectroradiometers. This data …
A survey on multi‐output regression
In recent years, a plethora of approaches have been proposed to deal with the increasingly
challenging task of multi‐output regression. This study provides a survey on state‐of‐the‐art …
challenging task of multi‐output regression. This study provides a survey on state‐of‐the‐art …
Data-driven decision making in precision agriculture: The rise of big data in agricultural systems
N Tantalaki, S Souravlas… - Journal of agricultural & …, 2019 - Taylor & Francis
In this paper, we provide a review of the research dedicated to applications of data science
techniques, and especially machine learning techniques, in relevant agricultural systems …
techniques, and especially machine learning techniques, in relevant agricultural systems …
Optical remote sensing and the retrieval of terrestrial vegetation bio-geophysical properties–A review
Forthcoming superspectral satellite missions dedicated to land monitoring, as well as
planned imaging spectrometers, will unleash an unprecedented data stream. The …
planned imaging spectrometers, will unleash an unprecedented data stream. The …
Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine
M Maimaitijiang, A Ghulam, P Sidike, S Hartling… - ISPRS Journal of …, 2017 - Elsevier
Estimating crop biophysical and biochemical parameters with high accuracy at low-cost is
imperative for high-throughput phenotyping in precision agriculture. Although fusion of data …
imperative for high-throughput phenotyping in precision agriculture. Although fusion of data …
Simultaneous corn and soybean yield prediction from remote sensing data using deep transfer learning
Large-scale crop yield estimation is, in part, made possible due to the availability of remote
sensing data allowing for the continuous monitoring of crops throughout their growth cycle …
sensing data allowing for the continuous monitoring of crops throughout their growth cycle …
Personalizing EEG-based affective models with transfer learning
Individual differences across subjects and nonstationary characteristic of
electroencephalography (EEG) limit the generalization of affective brain-computer interfaces …
electroencephalography (EEG) limit the generalization of affective brain-computer interfaces …
Hybrid machine learning algorithm and statistical time series model for network-wide traffic forecast
T Ma, C Antoniou, T Toledo - Transportation Research Part C: Emerging …, 2020 - Elsevier
We propose a novel approach for network-wide traffic state prediction where the statistical
time series model ARIMA is used to postprocess the residuals out of the fundamental …
time series model ARIMA is used to postprocess the residuals out of the fundamental …