28 citations · 106 across the 15 of their papers we have counts for
15 papers
Review of Kernel Learning for Intra-Hour Solar Forecasting with Infrared Sky Images and Cloud Dynamic Feature Extraction
Guillermo Terrén-Serrano, Manel Martínez-Ramón
The uncertainty of the energy generated by photovoltaic systems incurs an additional cost for a guaranteed, reliable supply of energy (i.e., energy storage). This investigation aim…
Detection of Clouds in Multiple Wind Velocity Fields using Ground-based Infrared Sky Images
Guillermo Terrén-Serrano, Manel Martínez-Ramón
Horizontal atmospheric wind shear causes wind velocity fields to have different directions and speeds. In images of clouds acquired using ground-based sky imagers, clouds may be mo…
Probabilistic analysis of solar cell optical performance using Gaussian processes
Rahul Jaiswal, Manel Martínez-Ramón, Tito Busani
This work investigates application of different machine learning based prediction methodologies to estimate the performance of silicon based textured cells. Concept of confidence b…
Wind Flow Estimation in Thermal Sky Images for Sun Occlusion Prediction
Guillermo Terrén-Serrano, Manel Martínez-Ramón
Moving clouds affect the global solar irradiance that reaches the surface of the Earth. As a consequence, the amount of resources available to meet the energy demand in a smart gri…
Geospatial Perspective Reprojections for Ground-Based Sky Imaging System
Guillermo Terrén-Serrano, Manel Martínez-Ramón
Sky imaging systems use lenses to acquire images concentrating light beams in a sensor. The light beams received by the sky imager have an elevation angle with respect to the devic…
Segmentation Algorithms for Ground-Based Infrared Cloud Images
Guillermo Terrén-Serrano, Manel Martínez-Ramón
The increasing number of Photovoltaic (PV) systems connected to the power grid are vulnerable to the projection of shadows from moving clouds. Global Solar Irradiance (GSI) forecas…
Explicit Basis Function Kernel Methods for Cloud Segmentation in Infrared Sky Images
Guillermo Terrén-Serrano, Manel Martínez-Ramón
Photovoltaic systems are sensitive to cloud shadow projection, which needs to be forecasted to reduce the noise impacting the intra-hour forecast of global solar irradiance. We pre…
Processing of Global Solar Irradiance and Ground-Based Infrared Sky Images for Solar Nowcasting and Intra-Hour Forecasting Applications
Guillermo Terrén-Serrano, Manel Martínez-Ramón
The projection of shadows from moving clouds in the troposphere impacts energy generation in power grids using photovoltaic systems. This investigation proposes an efficient method…
Data acquisition and image processing for solar irradiance forecasting
Guillermo Terrén-Serrano, Manel Martínez-Ramón
The energy available in Micro Grid (MG) that is powered by solar energy is tightly related to the weather conditions in the moment of generation. Very short-term forecast of solar…
Comparative Analysis of Methods for Cloud Segmentation in Ground-Based Infrared Images
Guillermo Terrén-Serrano, Manel Martínez-Ramón
The increasing penetration of photovoltaic systems in the power grid makes it vulnerable to cloud shadow projection. Real-time cloud segmentation in ground-based infrared images is…
Multi-Layer Wind Velocity Field Visualization in Infrared Images of Clouds for Solar Irradiance Forecasting
Guillermo Terrén-Serrano, Manel Martínez-Ramón
The energy available in a solar energy powered grid is uncertain due to the weather conditions at the time of generation. Forecasting global solar irradiance could address this pro…
An embedded deep learning system for augmented reality in firefighting applications
Manish Bhattarai, Aura Rose Jensen-Curtis, Manel MartíNez-Ramón
Firefighting is a dynamic activity, in which numerous operations occur simultaneously. Maintaining situational awareness (i.e., knowledge of current conditions and activities at th…
Time accelerated image super-resolution using shallow residual feature representative network
Meenu Ajith, Aswathy Rajendra Kurup, Manel Martínez-Ramón
The recent advances in deep learning indicate significant progress in the field of single image super-resolution. With the advent of these techniques, high-resolution image with hi…
Application of Gaussian Process Regression to Koopman Mode Decomposition for Noisy Dynamic Data
Akitoshi Masuda, Yoshihiko Susuki, Manel Martínez-Ramón +2
Koopman Mode Decomposition (KMD) is a technique of nonlinear time-series analysis that originates from point spectrum of the Koopman operator defined for an underlying nonlinear dy…
A Deep Learning Framework for Detection of Targets in Thermal Images to Improve Firefighting
Manish Bhattarai, Manel Martínez-Ramón
Intelligent detection and processing capabilities can be instrumental to improving the safety, efficiency, and successful completion of rescue missions conducted by firefighters in…