Sensors and Artificial Intelligence in Smart Agriculture

Dear Colleagues,

We seek manuscripts on advanced machine learning techniques and tools that extract knowledge and learn from large volumes of multimodal agricultural data. The following areas are of the highest interest:

• Multimodal/multisource data analytics techniques for precision agriculture (data obtained from wireless remote sensors, cameras, drones and databases with different spatial and temporal sampling patterns);
• New feature extraction and knowledge extraction tools that help identify the most discriminative variables for detection/classification purposes, as well as those variables correlated with the onset of pests and diseases;
• State-of-the-art machine learning tools for precision agriculture (deep neural networks for detection of pests and diseases, kernel methods for extraction nonlinear correlations among variables, and Gaussian processes to correlate and solve spatiotemporal regression problems involving multispectral images from drones and geotagged data from remote sensors).

Dr. Zoran Stamenkovic
Guest Editor

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