Results 71 to 80 of about 5,613,581 (365)

Segmentation of Moving Object Using Background Subtraction Method in Complex Environments [PDF]

Radioengineering, 2016
Background subtraction is an extensively used approach to localize the moving object in a video sequence. However, detecting an object under the spatiotemporal behavior of background such as rippling of water, moving curtain and illumination change or ...
S. Kumar, J. S. Yadav
doaj  

Optimal Techniques in Two-dimensional Spectroscopy: Background Subtraction for the 21st Century [PDF]

Publ.Astron.Soc.Pac.115:688-699,2003, 2003
In two-dimensional spectrographs, the optical distortions in the spatial and dispersion directions produce variations in the sub-pixel sampling of the background spectrum. Using knowledge of the camera distortions and the curvature of the spectral features, one can recover information regarding the background spectrum on wavelength scales much smaller ...
arxiv   +1 more source

Background subtraction and transient timing with Bayesian Blocks

, 2015
Aims: To incorporate background subtraction into the Bayesian Blocks algorithm so that transient events can be timed accurately and precisely even in the presence of a substantial, rapidly variable, background. Methods: We developed several modifications
Schwope, Axel D., Worpel, Hauke
core   +1 more source

The Saccharomyces cerevisiae amino acid transporter Lyp1 has a broad substrate spectrum

FEBS Letters, EarlyView.
In Saccharomyces cerevisiae, Yeast Amino acid Transporter family members mediate the import of amino acids, ranging from substrate specialists to generalists. Here, we show that the specialist transporter, Lyp1, has a broader substrate spectrum than previously described, with affinity constants spanning from micromolar to millimolar.
Foteini Karapanagioti, Sebastian Obermaier, Dirk J. Slotboom, Bert Poolman   +3 more
wiley   +1 more source

Dynamic Background Subtraction by Generative Neural Networks [PDF]

arXiv, 2022
Background subtraction is a significant task in computer vision and an essential step for many real world applications. One of the challenges for background subtraction methods is dynamic background, which constitute stochastic movements in some parts of the background. In this paper, we have proposed a new background subtraction method, called DBSGen,
arxiv  

Denoising-based Turbo Message Passing for Compressed Video Background Subtraction [PDF]

, 2020
In this paper, we consider the compressed video background subtraction problem that separates the background and foreground of a video from its compressed measurements. The background of a video usually lies in a low dimensional space and the foreground is usually sparse. More importantly, each video frame is a natural image that has textural patterns.
arxiv   +1 more source

A comparative study of circulating tumor cell isolation and enumeration technologies in lung cancer

Molecular Oncology, EarlyView.
Lung cancer cells were spiked into donor blood to evaluate the recovery rates of the following circulating tumor cell (CTC) enrichment technologies: CellMag™, EasySep™, RosetteSep™, Parsortix® PR1, and Parsortix® Prototype systems. Each method's advantages and disadvantages are described.
Volga M Saini, Ezgi Oner, Mark P. Ward, Sinead Hurley, Brian David Henderson, Faye Lewis, Stephen P. Finn, Gerard J. Fitzmaurice, John J. O'Leary, Sharon O'Toole, Lorraine O'Driscoll, Kathy Gately   +11 more
wiley   +1 more source

Combined spatially resolved metabolomics and spatial transcriptomics reveal the mechanism of RACK1‐mediated fatty acid synthesis

Molecular Oncology, EarlyView.
The authors analyzed the spatial distributions of gene and metabolite profiles in cervical cancer through spatial transcriptomic and spatially resolved metabolomic techniques. Pivotal genes and metabolites within these cases were then identified and validated.
Lixiu Xu, Jinqiu Li, Junqi Ma, Ayshamgul Hasim   +3 more
wiley   +1 more source

Combining Background Subtraction Algorithms with Convolutional Neural Network [PDF]

, 2018
Accurate and fast extraction of foreground object is a key prerequisite for a wide range of computer vision applications such as object tracking and recognition. Thus, enormous background subtraction methods for foreground object detection have been proposed in recent decades.
arxiv   +1 more source

Learning Spatial-Temporal Regularized Tensor Sparse RPCA for Background Subtraction [PDF]

arXiv, 2023
Video background subtraction is one of the fundamental problems in computer vision that aims to segment all moving objects. Robust principal component analysis has been identified as a promising unsupervised paradigm for background subtraction tasks in the last decade thanks to its competitive performance in a number of benchmark datasets.
arxiv