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Mario López, Noel Rodríguez and Gregorio Iglesias
To mitigate the effects of wind variability on power output, hybrid systems that combine offshore wind with other renewables are a promising option. In this work we explore the potential of combining offshore wind and solar power through a case study in ...
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Min Chang, Shuai Han, Guo Chen and Xuedian Zhang
Both noise and structure matter in single image super-resolution (SISR). Recent researches have benefited from a generative adversarial network (GAN) that promotes the development of SISR by recovering photo-realistic images. However, noise and structura...
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Sante Francesco Rende, Alessandro Bosman, Rossella Di Mento, Fabio Bruno, Antonio Lagudi, Andrew D. Irving, Luigi Dattola, Luca Di Giambattista, Pasquale Lanera, Raffaele Proietti, Luca Parlagreco, Mascha Stroobant and Emilio Cellini
In this study, we present a framework for seagrass habitat mapping in shallow (5?50 m) and very shallow water (0?5 m) by combining acoustic, optical data and Object-based Image classification. The combination of satellite multispectral images-acquired fr...
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Nancy Alvan Romero, Francesca Cigna and Deodato Tapete
The coastline environment and urban areas of Peru overlooking the Pacific Ocean are among the most affected by El Niño-Southern Oscillation (ENSO) events, and its cascading hazards such as floods, landslides and avalanches. In this work, the complete arc...
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Zetao Jiang, Yongsong Huang and Lirui Hu
The super-resolution generative adversarial network (SRGAN) is a seminal work that is capable of generating realistic textures during single image super-resolution. However, the hallucinated details are often accompanied by unpleasant artifacts. To furth...
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