Food security prediction from heterogeneous data combining machine and deep learning methods

Choosing the Best Sensor Fusion Method: A Machine-Learning Approach

(2020) Ramon F. Brena et al.   SENSORS

Using publicly available satellite imagery and deep learning to understand economic well-being in Africa

(2020) Christopher Yeh et al.   Nature Communications

Machine Learning-Based Ensemble Prediction of Water-quality Variables Using Feature-level and Decision-level Fusion with Proximal Remote Sensing

(2019) Kyle T. Peterson et al.   PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING

iFusion: Towards efficient intelligence fusion for deep learning from real-time and heterogeneous data

(2019) Kehua Guo et al.   Information Fusion

Time-series well performance prediction based on Long Short-Term Memory (LSTM) neural network model

(2019) Xuanyi Song et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

Multi-stage committee based extreme learning machine model incorporating the influence of climate parameters and seasonality on drought forecasting

(2018) Mumtaz Ali et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Methods for interpreting and understanding deep neural networks

(2018) Grégoire Montavon et al.   DIGITAL SIGNAL PROCESSING

Extreme learning machines with heterogeneous data types

(2018) Julio J. Valdés   NEUROCOMPUTING

Urban land-use mapping using a deep convolutional neural network with high spatial resolution multispectral remote sensing imagery

(2018) Bo Huang et al.   REMOTE SENSING OF ENVIRONMENT

A comparison of global agricultural monitoring systems and current gaps

(2018) Steffen Fritz et al.   AGRICULTURAL SYSTEMS

Detection of Brain Tumor based on Features Fusion and Machine Learning

(2018) Javeria Amin et al.   Journal of Ambient Intelligence and Humanized Computing

The Use of Support Vector Machine to Analyze Food Security in a Region of Brazil

(2016) Rommel Melgaço Barbosa et al.   APPLIED ARTIFICIAL INTELLIGENCE

Combining satellite imagery and machine learning to predict poverty

(2016) N. Jean et al.   SCIENCE

How do indicators of household food insecurity measure up? An empirical comparison from Ethiopia

(2014) Daniel Maxwell et al.   FOOD POLICY

What Are We Assessing When We Measure Food Security? A Compendium and Review of Current Metrics

(2013) Andrew D. Jones et al.   Advances in Nutrition

SUPERVISED LEARNING ALGORITHMS FOR FAMINE PREDICTION

(2011) Washington Okori et al.   APPLIED ARTIFICIAL INTELLIGENCE

Multisensor data fusion: A review of the state-of-the-art

(2011) Bahador Khaleghi et al.   Information Fusion