Nonnegative Tensor Factorization based on Low-Rank Subspace for Facial Expression Recognition
Sign Up to like & getrecommendations! Published in 2022 at "Mobile Networks and Applications"
DOI: 10.1007/s11036-020-01709-x
Abstract: Important progresses have been made in the field of artificial intelligence in recent years, and facial expression recognition (FER), which could greatly facilitate the development of human-computer interaction, has been becoming a significant research hotspot.… read more here.
Keywords: facial expression; tensor; low rank; subspace ... See more keywords
A Cooperative Spectrum Sensing Method Based on Soft Low-Rank Subspace Clustering
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2022.3174342
Abstract: When processing sensing signals under low signal-to-noise ratio environment, the sensing performance cannot be guaranteed in existing algorithms. To ensure sensing performance, we propose a novel spectrum sensing algorithm based on soft low-rank subspace clustering… read more here.
Keywords: spectrum sensing; based soft; low rank; rank subspace ... See more keywords
Atmospheric Column Water Vapor Retrieval From Hyperspectral VNIR Data Based on Low-Rank Subspace Projection
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2018.2816593
Abstract: The knowledge of atmospheric column water vapor concentration is crucial for compensating water absorption effects in remote sensing data. Several algorithms for the estimation of such a parameter were proposed in the past. One of… read more here.
Keywords: atmospheric column; water; water vapor; column water ... See more keywords
Fast and Latent Low-Rank Subspace Clustering for Hyperspectral Band Selection
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2019.2959342
Abstract: This article presents a fast and latent low-rank subspace clustering (FLLRSC) method to select hyperspectral bands. The FLLRSC assumes that all the bands are sampled from a union of latent low-rank independent subspaces and formulates… read more here.
Keywords: fast latent; low rank; subspace clustering; latent low ... See more keywords