Hyperspectral and Multispectral Image Fusion Via Self-Supervised Loss and Separable Loss
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3204769
Abstract: Fusion of hyperspectral images (HSIs) with low-spatial and high-spectral resolution and multispectral images (MSIs) with high-spatial and low-spectral resolution is an important method to improve spatial resolution. The existing deep-learning-based image fusion technologies usually neglect… read more here.
Keywords: loss; self supervised; image fusion; supervised loss ... See more keywords
RffAe-S: Autoencoder Based on Random Fourier Feature With Separable Loss for Unsupervised Signal Modulation Clustering
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3171349
Abstract: Unsupervised signal modulation clustering is becoming increasingly important due to its application in the dynamic spectrum access process of 5G wireless communication and threat detection at the physical layer of Internet of Things. The need… read more here.
Keywords: signal modulation; rffae; feature; unsupervised signal ... See more keywords