Inpainting of Remote Sensing SST Images With Deep Convolutional Generative Adversarial Network
Inpainting of Remote Sensing SST Images With Deep Convolutional Generative Adversarial Network is a scholarly work, published in 2019 in ''IEEE Geoscience and Remote Sensing Letters''. The main subjects of the publication include encoding, image, deep learning, noise reduction, artificial intelligence, data set, generative adversarial network, computer vision, super-resolution imaging, image fusion, inpainting, cloud computing, set, pattern recognition, point cloud, and computer science. The authors propose a new loss function for the inpainting network, which adds a supervision term to solve the authors' specific problem.