Local Normal Space Alignment for Industrial Process Monitoring by Nonisotropic Condition Data
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2025.3585208
Abstract: The effectiveness of dimension reduction analysis for high-dimensional process data is crucial to ensure industrial safety. Manifold learning methods can be advanced by considering both global and local data structures comprehensively, ensuring the capture of… read more here.
Keywords: local normal; process; process monitoring; normal space ... See more keywords
Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI With Sparse Sampling
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2022.3207774
Abstract: The spatial resolution and temporal frame-rate of dynamic magnetic resonance imaging (MRI) can be improved by reconstructing images from sparsely sampled ${k}$ -space data with mathematical modeling of the underlying spatiotemporal signals. These models include… read more here.
Keywords: dynamic mri; linear tangent; space; space alignment ... See more keywords
DSAF: Dual Space Alignment Framework for Visible-Infrared Person Re-Identification
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Multimedia"
DOI: 10.1109/tmm.2025.3542988
Abstract: Visible-infrared person re-identification (VI-ReID) is a cross-modality retrieval task that aims to match visible and infrared pedestrian images across non-overlapped cameras. However, we observe that three crucial challenges remain inadequately addressed by existing methods: (i)… read more here.
Keywords: modality; space; visible infrared; dual space ... See more keywords