Results 61 to 70 of about 871,644 (244)
Archetypal Analysis and Structured Sparse Representation for Hyperspectral Anomaly Detection
Remote Sensing, 2021 Hyperspectral images (HSIs) often contain pixels with mixed spectra, which makes it difficult to accurately separate the background signal from the anomaly target signal.
Genping Zhao +4 more
doaj +1 more source
Spectral Unmixing via Data-Guided Sparsity [PDF]
IEEE Transactions on Image Processing, 2014 Hyperspectral unmixing, the process of estimating a common set of spectral bases and their corresponding composite percentages at each pixel, is an important task for hyperspectral analysis, visualization and understanding. From an unsupervised learning perspective, this problem is very challenging---both the spectral bases and their composite ...
Feiyun Zhu +5 more
openaire +3 more sources
Advanced Science, EarlyView.A minimally invasive optical window enables stable, long‐term imaging of peripheral nerves in vivo at single‐axon resolution. Dynamic processes of degeneration, regeneration, and cellular remodeling are visualized across multiple time scales within the same nerve region, providing a unique platform to study a variety of anatomical and molecular events ...
Igor D. Luzhansky +15 more
wiley +1 more source
Hyperspectral Image Resolution Enhancement Based on Spectral Unmixing and Information Fusion [PDF]
, 2011 Hyperspectral imaging sensors exibit high spectral resolution, but normally low spatial resolution. This leads to spectral signatures of pixels originating from different object types. Such pixels are called mixed pixels.
Avbelj, Janja +4 more
core
Remote Sensing, 2018 Spectral unmixing is a popular technique for hyperspectral data interpretation. It focuses on estimating the abundance of pure spectral signature (called as endmembers) in each observed image signature.
Xiangrong Zhang +6 more
doaj +1 more source
Advanced Science, EarlyView.Cartilage injury promotes local fibrinogen deposition, which accelerates monosodium urate crystallization and activates integrin‐mediated matrix‐degradation. This self‐amplifying cycle drives gout‐related cartilage erosion. Disrupting fibrinogen deposition or restoring the cartilage barrier could interrupt this vicious cycle.
Hanlin Xu +7 more
wiley +1 more source
Bayesian estimation of linear mixtures using the normal compositional model. Application to hyperspectral imagery [PDF]
, 2010 This paper studies a new Bayesian unmixing algorithm for hyperspectral images. Each pixel of the image is modeled as a linear combination of so-called endmembers.
Eches, Olivier +3 more
core +1 more source
From Berzelius to Hyperspace: Previously Unrecognized Network of Reactivity in Textbook Brominations
Angewandte Chemie, EarlyView.Robotic scans across multidimensional condition spaces of classic bromination reactions uncover regions of previously unrecognized reactivity, yielding new major products and novel substitution patterns. Correlation and anticorrelation analyses of product distributions across these hyperspaces enable reconstruction of the underlying mechanistic ...
Yankai Jia +9 more
wiley +2 more sources
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingIn recent years, hyperspectral sparse unmixing (HSU) has garnered extensive research and attention due to its unique characteristic of not requiring the estimation of endmembers and their number.
Kewen Qu +3 more
doaj +1 more source
Preserving Motor Features by Alternative Re‐Referencing to Remove Heart Artifact on the Stentrode
Advanced Science, EarlyView.Endovascular brain‐computer interfaces record neural activity from within cerebrovasculature, at the expense of electrocardiogram contamination. Band‐limited independent component analysis separates this heart‐based artifact from task‐relevant neural activity in each frequency band, enabling the reconstruction of cleaner neural recordings without the ...
Ariel K. Feldman +11 more
wiley +1 more source