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Quantifying the sensitivity limit of ICG imaging in the presence of tissue autofluorescence. [PDF]
J Biomed OptBelozerov Y, Ripoll J, Turchin I.
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Methods for Evaluating Models, Tests And Biomarkers (MEMTAB): Abstracts from the 7<sup>th</sup> International Conference, MEMTAB 2025. [PDF]
Diagn Progn Reseuropepmc +1 more source
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A hybrid codebook background model for background subtraction
2011 IEEE Workshop on Signal Processing Systems (SiPS), 2011Real-time segmentation of scene into foreground and background is an important issue for many applications. Different from previous codebook (CB) methods, this paper introduces a hybrid CB model by combining the mixture of Gaussian (MOG) method and the CB method.
I-Ting Sun +2 more
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Background modeling for generative image models
Computer Vision and Image Understanding, 2015Discussion of the implicit but unavoidable background model in generative image models.Analysis of common practical strategies to deal with the problem and their drawbacks.Explicit background models are proposed as a fundamental solution.The background model is introduced through an efficient likelihood ratio correction.The background correction ...
Sandro Schönborn +3 more
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Background modeling in the maritime domain
Machine Vision and Applications, 2013Maritime environment represents a challenging scenario for automatic video surveillance due to the complexity of the observed scene: waves on the water surface, boat wakes, and weather issues contribute to generate a highly dynamic background. Moreover, an appropriate background model has to deal with gradual and sudden illumination changes, camera ...
Domenico Daniele Bloisi +2 more
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A Fluid Background Traffic Model
2009 IEEE International Conference on Communications, 2009Background traffic has a significant impact on the behavior of network services and protocols. However, a detailed model of the background traffic can be extremely time consuming in simulation. In this paper, we extend our previous hybrid model that combines fluid and packet-oriented characterization of network traffic for a realistic representation of
Ting Li 0024, Jason Liu 0001
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Stochastic approximation for background modelling
Computer Vision and Image Understanding, 2011Many background modelling approaches are based on mixtures of multivariate Gaussians with diagonal covariance matrices. This often yields good results, but complex backgrounds are not adequately captured, and post-processing techniques are needed.
Ezequiel López-Rubio +1 more
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Scale-Corrected Background Modeling
2017 14th Conference on Computer and Robot Vision (CRV), 2017Modern security cameras are capable of capturing high-resolution HD or 4K videos and support embedded analytics capable of automatically tracking objects such as people and cars moving through the scene. However, due to a lack of computational power on these cameras, the embedded video analytics cannot utilize the full available video resolution ...
Parthipan Siva, Michael Jamieson
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Aggregated Dynamic Background Modeling
2006 International Conference on Image Processing, 2006Standard practices in background modeling learn a separate model for every pixel in the image. However, in dynamic scenes the connection between an observation and the place where it was observed is much less important and is usually random. For example, a wave observed in an ocean scene could easily have been observed at another place in the image ...
Amit Adam, Ehud Rivlin, Ilan Shimshoni
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2016
This chapter contextualizes the role of smart meters in smart grid initiatives around the world to show that the smart grid concept goes beyond energy supplier modernization. In addition, this chapter presents the security model and the privacy model for Privacy-Preserving Protocols (PPPs).
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This chapter contextualizes the role of smart meters in smart grid initiatives around the world to show that the smart grid concept goes beyond energy supplier modernization. In addition, this chapter presents the security model and the privacy model for Privacy-Preserving Protocols (PPPs).
openaire +1 more source