Results 111 to 120 of about 55,457 (295)

Intersecting Faces: Non-negative Matrix Factorization With New Guarantees

, 2015
Non-negative matrix factorization (NMF) is a natural model of admixture and is widely used in science and engineering. A plethora of algorithms have been developed to tackle NMF, but due to the non-convex nature of the problem, there is little guarantee ...
Ge, Rong, Zou, James
core  

Bioanalytical TERS and Advanced Data Processing Methods

Journal of Raman Spectroscopy, EarlyView.
Tip‐enhanced Raman spectroscopy delivers label‐free, subnanometer vibrational imaging of biological systems. Recent advances in instrumentation, data analysis, and ambient/liquid operation enable surface‐selective mapping of molecular heterogeneity in proteins, nucleic acids, membranes, and viruses, positioning TERS as a powerful platform for nanoscale
Sarika Joshi, Ankit Dodla, Sarthak Saxena, Twinkle Soni, Sumit Saxena, Shobha Shukla, Bayden R. Wood   +6 more
wiley   +1 more source

Symmetric Nonnegative Matrix Factorization Based on Box-Constrained Half-Quadratic Optimization

IEEE Access, 2020
Nonnegative Matrix Factorization (NMF) based on half-quadratic (HQ) functions was proven effective and robust when dealing with data contaminated by continuous occlusion according to the half-quadratic optimization theory.
Bo-Wei Chen
doaj   +1 more source

Startups Driving Artificial Intelligence Into Clinical Dermatology

JEADV Clinical Practice, EarlyView.
ABSTRACT Artificial intelligence (AI) is rapidly transitioning from innovation to routine clinical application in dermatology. This review examines how AI‐enabled technologies are being developed and integrated across diverse clinical purposes and workflows.
Dominique Du Crest, Benjamin Miguel Monteagudo, Stanislas Vandier, Mullarkey Dan, Svedenhag Per, Jon Friis, Monisha Madhumita, Lilit Garibyan, Tu‐Anh Duong, Merete Haedersdal, Vinzent Kevin Ortner   +10 more
wiley   +1 more source

Inertia-Constrained Pixel-by-Pixel Nonnegative Matrix Factorisation: A Hyperspectral Unmixing Method Dealing with Intra-Class Variability

Remote Sensing, 2018
Blind source separation is a common processing tool to analyse the constitution of pixels of hyperspectral images. Such methods usually suppose that pure pixel spectra (endmembers) are the same in all the image for each class of materials.
Charlotte Revel, Yannick Deville, Véronique Achard, Xavier Briottet, Christiane Weber   +4 more
doaj   +1 more source

Underdetermined blind source separation based on Fuzzy C-Means and Semi-Nonnegative Matrix Factorization [PDF]

, 2012
Conventional blind source separation is based on over-determined with more sensors than sources but the underdetermined is a challenging case and more convenient to actual situation.
Alshabrawy, Ossama S., Awad, W. A., Ghoneim, M. E., Hassanien, Aboul Ella   +3 more
core   +1 more source

Individual movement modeling expands the power of migratory species observations: North Atlantic right whale case study

Limnology and Oceanography: Methods, EarlyView.
Abstract Understanding a population's distribution depends on observing the presence and movement of individuals throughout their range. For highly mobile marine species, these observations typically rely on high effort monitoring programs. Tracking enough individuals to understand trends in movement behavior is not always logistically feasible, and ...
Abigail M. Kreuser, Daniel E. Pendleton, Nicholas R. Record, Erin L. Meyer‐Gutbrod   +3 more
wiley   +1 more source

Clinical Outcome Assessments in Parkinson's Disease: A Scoping Review of Current Rating Scales and Future Needs

Movement Disorders Clinical Practice, EarlyView.
Abstract Background Clinical outcome assessments (COAs) are essential for evaluating symptom severity, treatment response, and disease progression in Parkinson's disease (PD). As clinical knowledge evolves, it is necessary to revisit the recommendation status on the COAs to ensure their continued relevance and validity. Objectives To provide an updated
Evita Papathoma, Panagiota Tsitsi, Nirosen Vijiaratnam, Camila Aquino, Stephen R. Duma, Norbert Kovacs, Kigocha Lameck Okeng'o, Aparna Wagle Shukla, Roongroj Bhidayasiri, Tiago A. Mestre, Alvaro Sanchez Ferro, Alberto J. Espay, Michelle H.S. Tosin, Matej Skorvanek, Ioanna Markaki   +14 more
wiley   +1 more source

Spectro-temporal post-enhancement using MMSE estimation in NMF based single-channel source separation [PDF]

, 2013
We propose to use minimum mean squared error (MMSE) estimates to enhance the signals that are separated by nonnegative matrix factorization (NMF). In single channel source separation (SCSS), NMF is used to train a set of basis vectors for each source ...
Erdogan, Hakan, Erdoğan, Hakan, Grais, Emad Mounir   +2 more
core   +1 more source

Mean Field Theory For Non-Equilibrium Network Reconstruction

, 2011
There has been recent progress on the problem of inferring the structure of interactions in complex networks when they are in stationary states satisfying detailed balance, but little has been done for non-equilibrium systems.
Hertz, John A., Roudi, Yasser
core   +1 more source