Correntropy-Based Autoencoder-Like NMF With Total Variation for Hyperspectral Unmixing
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2020.3020896
Abstract: In order to unmix the hyperspectral imagery (HSI) with better performance, this letter proposes a correntropy-based autoencoder-like nonnegative matrix factorization (NMF) (CANMF) with total variation (CANMF-TV) method. NMF is extensively applied to unmix the mixed… read more here.
Keywords: total variation; like nmf; autoencoder like; autoencoder ... See more keywords
Community Detection via Autoencoder-Like Nonnegative Tensor Decomposition.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3201906
Abstract: Community detection aims at partitioning a network into several densely connected subgraphs. Recently, nonnegative matrix factorization (NMF) has been widely adopted in many successful community detection applications. However, most existing NMF-based community detection algorithms neglect… read more here.
Keywords: autoencoder like; decomposition; tensor; community detection ... See more keywords
Latent Factor Decoding of Multi-Channel EEG for Emotion Recognition Through Autoencoder-Like Neural Networks
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2020.00087
Abstract: Robust cross-subject emotion recognition based on multichannel EEG has always been hard work. In this work, we hypothesize that there exist default brain variables across subjects in emotional processes. Hence, the states of the latent… read more here.
Keywords: recognition; like neural; autoencoder like; emotion recognition ... See more keywords