921 resultados para Statistical Pattern Recognition
Resumo:
This paper presents an innovative approach for signature verification and forgery detection based on fuzzy modeling. The signature image is binarized and resized to a fixed size window and is then thinned. The thinned image is then partitioned into a fixed number of eight sub-images called boxes. This partition is done using the horizontal density approximation approach. Each sub-image is then further resized and again partitioned into twelve further sub-images using the uniform partitioning approach. The features of consideration are normalized vector angle (α) from each box. Each feature extracted from sample signatures gives rise to a fuzzy set. Since the choice of a proper fuzzification function is crucial for verification, we have devised a new fuzzification function with structural parameters, which is able to adapt to the variations in fuzzy sets. This function is employed to develop a complete forgery detection and verification system.
Resumo:
These are the full proceedings of the conference.
Resumo:
Rapid clearance of dying cells is a vital feature of apoptosis throughout development, tissue homeostasis and resolution of inflammation. The phagocytic removal of apoptotic cells is mediated by both professional and amateur phagocytes, armed with a series of pattern recognition receptors that participate in host defence and apoptotic cell clearance. CD14 is one such molecule. It is involved in apoptotic cell clearance (known to be immunosuppressive and anti-inflammatory) and binding of the pathogen-associated molecular pattern, lipopolysaccharides (a pro-inflammatory event). Thus CD14 is involved in the assembly of two distinct ligand-dependent macrophage responses. This project sought to characterise the involvement of the innate immune system, particularly CD14, in the removal of apoptotic cells. The role of non-myeloid CD14 was also considered and the data suggests that the expression of CD14 by phagocytes may define their professional status as phagocytes. To assess if differential CD14 ligation causes the ligand-dependent divergence in macrophage responses, a series of CD14 point mutants were used to map the binding of apoptotic cells and lipopolysaccharides. Monoclonal antibodies, 61D3 and MEM18, known to interfere with ligand-binding and responses, were also mapped. Data suggests that residue 11 of CD14, is key for the binding of 61D3 (but not MEM18), LPS and apoptotic cells, indicating lipopolysaccharides and apoptotic cells bind to similar residues. Furthermore using an NF-kB reporter, results show lipopolysaccharides but not apoptotic cells stimulate NF-kB. Taken together these data suggests ligand-dependent CD14 responses occur via a mechanism that occurs downstream of CD14 ligation but upstream of NF-?B activation. Alternatively apoptotic cell ligation of CD14 may not result in any signalling event, possibly by exclusion of TLR-4, suggesting that engulfment receptors, (e.g. TIM-4, BAI1 and Stablin-2) are required to mediate the uptake of apoptotic cells and the associated anti-inflammatory response.
Resumo:
The generative topographic mapping (GTM) model was introduced by Bishop et al. (1998, Neural Comput. 10(1), 215-234) as a probabilistic re- formulation of the self-organizing map (SOM). It offers a number of advantages compared with the standard SOM, and has already been used in a variety of applications. In this paper we report on several extensions of the GTM, including an incremental version of the EM algorithm for estimating the model parameters, the use of local subspace models, extensions to mixed discrete and continuous data, semi-linear models which permit the use of high-dimensional manifolds whilst avoiding computational intractability, Bayesian inference applied to hyper-parameters, and an alternative framework for the GTM based on Gaussian processes. All of these developments directly exploit the probabilistic structure of the GTM, thereby allowing the underlying modelling assumptions to be made explicit. They also highlight the advantages of adopting a consistent probabilistic framework for the formulation of pattern recognition algorithms.
Resumo:
A practical Bayesian approach for inference in neural network models has been available for ten years, and yet it is not used frequently in medical applications. In this chapter we show how both regularisation and feature selection can bring significant benefits in diagnostic tasks through two case studies: heart arrhythmia classification based on ECG data and the prognosis of lupus. In the first of these, the number of variables was reduced by two thirds without significantly affecting performance, while in the second, only the Bayesian models had an acceptable accuracy. In both tasks, neural networks outperformed other pattern recognition approaches.
Resumo:
Digital watermarking aims at embedding information in digital data. The watermark is usually required to be imperceptible, unremovable and to have a high information content. Unfortunately, these three requirements are contradicting. For example, having a more robust watermark makes it either more perceptible or/and less informative. For Gaussian data and additive white Gaussian noise, an optimal but also impractical scheme has already be devised. Since then, many practical schemes have tried to approach the theoretical limits. This paper investigate improvements to current state-of-the-art embedding schemes.
Resumo:
A recently proposed colour based tracking algorithm has been established to track objects in real circumstances [Zivkovic, Z., Krose, B. 2004. An EM-like algorithm for color-histogram-based object tracking. In: Proc, IEEE Conf. on Computer Vision and Pattern Recognition, pp. 798-803]. To improve the performance of this technique in complex scenes, in this paper we propose a new algorithm for optimally adapting the ellipse outlining the objects of interest. This paper presents a Lagrangian based method to integrate a regularising component into the covariance matrix to be computed. Technically, we intend to reduce the residuals between the estimated probability distribution and the expected one. We argue that, by doing this, the shape of the ellipse can be properly adapted in the tracking stage. Experimental results show that the proposed method has favourable performance in shape adaption and object localisation.
Resumo:
Apoptosis, programmed cell death, is used by multicellular organisms to remove cells that are in excess, damaged or diseased. Activation of the apoptosis programme generates "eat me" signals on the surface of the apoptotic cell that mediate recognition and clearance by the innate immune system. CD14, a pattern recognition receptor expressed on macrophages, is widely known for its ability to recognise the pathogen-associated molecular pattern lipopolysaccharide (LPS) and promote inflammation. However, CD14 has also been shown to mediate binding and removal of apoptotic cells in a process that is anti-inflammatory suggesting CD14 is capable of producing two distinct, ligand-dependent macrophage responses. Whilst the molecular basis for this dichotomy has yet to be defined it is clear that CD14 defines a point of interest on the macrophage surface where we may study ligand-specific responses of macrophages. Our work seeks to define the molecular mechanisms underlying the involvement of CD14 in the non-inflammatory clearance of apoptotic cells. Here we used three different differentiation strategies to generate macrophages from the monocytic cell line THP-1. The resultant macrophage models were characterised to assess the expression and function of CD14 within each model system. Whilst each macrophage model shows increased levels of surface CD14 expression, our results demonstrate significant differences in the various models’ abilities to respond to LPS and clear apoptotic cells in a CD14-dependent manner. TLR4 levels correlated positively with LPS responsiveness but not CD14-dependent apoptotic cell clearance or anti-inflammatory responses to apoptotic cells. These observations suggest CD14-dependent apoptotic cell clearance is not dependent on TLR4. Taken together our data support the notion that the CD14 ligand-dependent responses to LPS and apoptotic cells derive from changes at the macrophage surface. The nature and composition of the CD14-co-receptor complex for LPS and apoptotic cell binding and responses is the subject of further study.
Resumo:
Rapid elimination of cells undergoing programmed cell death (apoptosis) is vital to maintain tissue homeostasis. The phagocytic removal of apoptotic cells (AC) is mediated by innate immune molecules, professional phagocytes and amateur phagocytes that recognise "eat me" signals on the surface of the AC. CD14, a pattern recognition receptor expressed on macrophages, is widely known for its ability to recognise the pathogen-associated molecular pattern lipopolysaccharide (LPS) and promote inflammation. CD14 also mediates the binding and removal of AC, a process that is considered to be anti-inflammatory therefore suggesting CD14 is capable of producing two distinct ligand-dependent responses. Our work seeks to define the molecular mechanisms underlying the involvement of CD14 in the non-inflammatory clearance of AC. Here we describe three different differentiation strategies used to generate macrophages from the monocytic cell line THP-1. Whilst CD14 expression was increased in each macrophage model we demonstrate significant differences in the various macrophage models' abilities to respond to LPS and clear AC. We show that CD14 expression correlates with CD14-dependent AC clearance and anti-inflammatory responses to AC. However LPS responsiveness correlates, as expected, with TLR4 but not CD14 expression. These observations suggest CD14-dependent AC clearance is not dependent on TLR4. Taken together our data support the notion that CD14 ligand-dependent responses to LPS and AC are derived from changes at the macrophage surface. The nature and composition of the CD14-co-receptor complex for LPS and AC binding and consequent responses is the subject of further study.