1,720,963 research outputs found
Bayesian Conditioning for estimating the relative degrees of Reliability in a group of Neural Networks engaged at Iris Biometric Identification
No full textThe main problem with iris biometric identification systems is the presence of noises in the image of the eye (eyelid, eyelashes, etc...). To remove it many authors apply appropriate preprocessing to the image, but unfortunately this yields losses of information. Our work aims at correctly recognizing the subject also in presence of high rates of noise. The basic idea is that of partitioning the image of iris into 8 not-interleaved segments of the same size. Each segment is given to an LVQ network which generates prototypes with a high resistance to noise. Notwithstanding this, the 8 LVQ nets may still disagree in identifying the subject. In this paper we apply a method developed by the “belief revision” community to identify conflicts and rearrange the degrees of reliability of each expert (the LVQ nets) through a Bayesian algorithm. This estimated ranking of reliability is useful to take the final decision. Our work has produced an interesting 84 % of positive identificat..
Conflict Detection and Bayesian Conditioning for Estimating the Reliability of Each LVQ Network in a Group Engaged at Iris Biometric Identification
No full textThe main problem with iris biometric identification systems is the presence of noises in the image of the eye (eyelid, eyelashes, etc...). To remove it many authors apply appropriate preprocessing to the image, but unfortunately this yields losses of information. Our work aims at correctly recognizing the subject also in presence of high rates of noise. The basic idea is that of partitioning the image of iris into 8 not-interleaved segments of the same size. Each segment is given to an LVQ network which generates prototypes with a high resistance to noise. Notwithstanding this, the 8 LVQ nets may still disagree in identifying the subject. In this paper we apply a method developed by the "belief revision" community to identify conflicts and rearrange the degrees of reliability of each expert (the LVQ nets) through a Bayesian algorithm. This estimated ranking of reliability is useful to take the final decision
Hybrid System for a Never-Ending Unsupervised Learning
No full textWe propose a Hybrid System for dynamic environments, where a “Multiple Neural Networks” system works with Bayes Rule. One or more neural nets may no longer be able to properly operate, due to partial changes in some of the characteristics of the individuals. We assume that each expert network has a reliability factor that can be dynamically re-evaluated on the ground of the global recognition operated by the overall group. Since the net's degree of reliability is defined as the probability that the net is giving the desired output, in case of conflicts between the outputs of the various nets the re-evaluation of their degrees of reliability can be simply performed on the basis of the Bayes Rule. The new vector of reliability will be used for making the final choice, by applying two algorithms, the “Inclusion based” and the “Weighted” one over all the maximally consistent subsets of the global outcome
Multiple Neural Networks and Bayesian Belief Revision for a never-ending unsupervised learning
No full textA system of Multiple Neural Networks has been proposed to solve the face recognition problem. Our idea is that a set of expert networks specialized to recognize specific parts of face are better than a single network. This is because a single network could no longer be able to correctly recognize the subject when some characteristics partially change. For this purpose we assume that each network has a reliability factor defined as the probability that the network is giving the desired output. In case of conflicts between the outputs of the networks the reliability factor can be dynamically re-evaluated on the base of the Bayes Rule. The new reliabilities will be used to establish who is the subject. Moreover the network disagreed with the group and specialized to recognize the changed characteristic of the subject will be retrained and then forced to correctly recognize the subject. Then the system is subjected to continuous learning
Ultrastructural computerized morphometry of platelets in chronic myelogenous leukemia making use of ultra-thin sections and freeze-fracture procedure. A preliminary approach
No full textBiochemical and morphological data have shown that the circulating platelets are deeply altered in patients with chronic myelogenous leukemia. In this report we describe the results of ultrastructural morphometry performed by means of a computerized device of the platelet shape (ultra-thin sectioned platelets) and of the platelet plasma-membrane (freeze-fractured platelets). Platelets appeared deeply modified: reduced mean platelet area and perimeter, increased surface density of the openings of the surface connected canalicular system, abnormal features of the platelet cytoplasm and some aspects of platelets joined together even if with heterogeneity in these findings did appear from patient to patient
Multiple neural networks system for dynamic environments
No full textWe propose a “Multiple Neural Networks” system for dynamic environments, where one or more neural nets may no longer be able to properly operate, due to sensible partial changes in the characteristics of the individuals. We assume that each expert network has a reliability factor that can be dynamically re-evaluated on the ground of the global recognition operated by the overall group. Since the net’s “degree of reliability” is defined as “the probability that the net is giving the desired output”, in case of conflicts between the outputs of the various nets the re-evaluation of their “degrees of reliability” can be simply performed on the basis of the Bayes Rule. The new vector of reliability will be used for making the final choice, by applying the “Inclusion based” algorithm over all the maximally consistent subsets of the global outcome. Finally, the nets recognized as responsible for the conflicts will be automatically forced to learn about the changes in the individuals’ characteristics and avoid to make the same error in the immediate futur
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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