Results 21 to 30 of about 22,937 (263)
Combinatorial Regression and Improved Basis Pursuit for Sparse Estimation [PDF]
, 2012 Sparse representations accurately model many real-world data sets. Some form of sparsity is conceivable in almost every practical application, from image and video processing, to spectral sensing in radar detection, to bio-computation and genomic signal ...
Khajehnejad, M. Amin
core +1 more source
Kinetic Compressive Sensing [PDF]
2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2017 5 pages, 6 figures, Submitted to the Conference Record of "IEEE Nuclear Science Symposium and Medical Imaging Conference (IEEE NSS-MIC) 2017"
Scipioni Michele +6 more
openaire +3 more sources
Applied and Computational Harmonic Analysis, 2023 We introduce the broad subclass of algebraic compressed sensing problems, where structured signals are modeled either explicitly or implicitly via polynomials. This includes, for instance, low-rank matrix and tensor recovery. We employ powerful techniques from algebraic geometry to study well-posedness of sufficiently general compressed sensing ...
Breiding, Paul +3 more
openaire +2 more sources
Perceptual Compressive Sensing [PDF]
, 2018 Accepted by The First Chinese Conference on Pattern Recognition and Computer Vision (PRCV 2018). This is a pre-print version (not final version)
Jiang Du 0011 +3 more
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Blind Compressed Sensing [PDF]
IEEE Transactions on Information Theory, 2011 The fundamental principle underlying compressed sensing is that a signal, which is sparse under some basis representation, can be recovered from a small number of linear measurements. However, prior knowledge of the sparsity basis is essential for the recovery process.
Sivan Gleichman, Yonina C. Eldar
openaire +2 more sources
Tumour–host interactions in Drosophila: mechanisms in the tumour micro‐ and macroenvironment
Molecular Oncology, EarlyView.This review examines how tumour–host crosstalk takes place at multiple levels of biological organisation, from local cell competition and immune crosstalk to organism‐wide metabolic and physiological collapse. Here, we integrate findings from Drosophila melanogaster studies that reveal conserved mechanisms through which tumours hijack host systems to ...
José Teles‐Reis, Tor Erik Rusten
wiley +1 more source
New Face Representation Using Compressive Sensing [PDF]
, 2011 In this paper we present a new descriptor for representing face images. We used compressive sensing concept to prepare a Gaussian Random or Binary Random Measurement Matrix (GRMM). We simply project the face images to new space using GRMM. Classification
A. Enis Cetin +6 more
core +1 more source
FEBS Open Bio, EarlyView.Unique biological samples, such as site‐specific mutant proteins, are available only in limited quantities. Here, we present a polarization‐resolved transient infrared spectroscopy setup with referencing to improve signal‐to‐noise tailored towards tracing small signals. We provide an overview of characterizing the excitation conditions for polarization‐
Clark Zahn, Karsten Heyne
wiley +1 more source
Quantization and Compressive Sensing [PDF]
, 2015 35 pages, 20 figures, to appear in Springer book "Compressed Sensing and Its Applications ...
Boufounos, Petros +3 more
openaire +3 more sources
RoundMi: A quantitative method to analyze mitochondrial morphology in mitotic cells
FEBS Open Bio, EarlyView.RoundMi is a workflow for rapid analysis of mitochondrial morphology in mitotic cells. By combining adaptive preprocessing with automated segmentation and quantification, it enables accurate measurements from single focal plane images, reducing acquisition time and computational demands while remaining compatible with high‐throughput fixed and live ...
Elmira Parvindokht Bararpour +2 more
wiley +1 more source