Statistical Analysis of Designed Experiments, Third Edition

Toutenburg, Helge; Shalabh,

doi:10.1007/978-1-4419-1148-3

Cited by 64 publications

(69 citation statements)

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“…In order to validate our results and the performance of the ICC algorithm proposed here, we evaluated the statistical significance of the error rates for the context-independent classification (ε ci ) versus that obtained after the application of the ICC algorithm (ε cd ) [27]. We Table 2 the summary of results for our work; a multilayer perceptron with a reduced-sized output layer proposed in [11]; a standard multilayer perceptron with one hidden layer proposed in [10]; and a hierarchical system that classifies the patterns firstly in 7 major groups of classes, and then in one of the 24 karyotype classes, proposed in [16].…”

Section: Resultsmentioning

confidence: 92%

Iterative Contextual Recurrent Classification of Chromosomes

Martínez

Juan

Casacuberta

2007

Neural Process Lett

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Recurrent connectionist models provide a method to represent dynamic patterns in a neural network. In this work we present a method for chromosome classification based on an almost unexplored neural network technique for this task. A partially recurrent connectionist model, the Elman network, is managed to capture the dark and light band patterns of the different classes. The proposed method is completed with the formulation of the ICC (iterative contextual classification) algorithm in order to restrict the classification to the cell context, and is applied to the neural network results. The Copenhagen data set was used in the experiments, where a cross-validation method was applied in order to obtain statistically representative results using the complete corpus. The entire system obtained very good results for this task, improving the performance of other neural network approaches.

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Section: Resultsmentioning

confidence: 92%

Iterative Contextual Recurrent Classification of Chromosomes

Martínez

Juan

Casacuberta

2007

Neural Process Lett

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“…In the case of the experimented data, noise is not important in the audio signals, so the inclusion of the derivatives only results in greater complexity of the classifier, without adding meaningful information for discriminating the emotions. The statistical significance of the results was evaluated considering the probability that the classification error of a given classifier ε (deep network) is smaller than the one of the reference system ε re f (MLP) [16]. The statistical independence of the errors for each pattern was assumed and the binomial distribution of the errors was modeled by means of a Gaussian distribution.…”

Section: Experiments and Resultsmentioning

confidence: 99%

Multimodal Emotion Recognition Using Deep Networks

et al. 2015

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Abstract-In the last years, several efforts have been devoted to the automatic recognition of human emotions. On the one side, there are several works based on speech processing and on the other side, using facial expressions in still images. More recently, other modalities such as body gestures, biosignals and others have been started to be used. In this work we present a multimodal system that process audiovisual information, exploiting the prosodic features in the speech and the development of the facial expressions in videos. The classification of the video in one of six emotions is carried out by deep networks, a neural network architecture consisting of several layers that capture high-order correlations betwen the features. The obtained results show the suitability of the proposed approach for this task, improving the performance of standard multilayer Perceptrons.

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“…According to the value of variance, the t-test (if variances were equal) or Cochran and Cox tests (if variances were not equal) were used to study the differences between mean measures of teeth (Snedecor & Cochran, 1972;Toutenburg, 2002). For each comparison, the effect size (ES) per Cohen's d value (standardized difference between two groups) was measured.…”

Section: Methodsmentioning

confidence: 99%

The Metric Features of Teeth in Female-to-Male Transsexuals

2008

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The aim of the study was to evaluate the odontometric characteristics of female-to-male transsexuals (FtM) in comparison to control groups of males and females. A total of 48 FtM, aged 20-28 years, were studied. For each tooth, two standard measurements were taken: the mesiodistal (MD) and the buccolingual (BL) diameter of the crown. Significant differences between males and females were found in BL measures of all maxillary teeth as well as mandibular lateral incisor and canine. Within the MD measures, the most distinguishing were maxillary and mandibular canines and the first molars. For seven teeth, there were a total of 14 comparisons of MD (half for the maxilla and half for the mandible) between the control men and women. Of these, the men had larger diameters for 12, of which four were statistically significant. There were also a total of 14 comparisons of BL diameter; of these, the men had larger diameters for 13, of which nine were statistically significant. For seven teeth, there were a total of 14 comparisons of MD between the control men and the FtM. Of these, the men had larger diameters for 12, of which seven were statistically significant. There were also 14 comparisons of BL; of these, the men had larger diameters for 10, of which six were statistically significant. For seven teeth, there were a total of 14 comparisons of MD between the control women and the FtM. Of these, the women had larger diameters for nine, of which three were statistically significant. There were also a total of 14 comparisons of BL; of these, the FtM had larger diameters for 13, of which five were statistically significant. Our study revealed that the shift of values of metric features in teeth of FtM towards males was more frequent in the more sexually dimorphic BL diameters characterized by significantly greater width of the crown of five teeth: maxillary canine, first and second molars, as well as mandibular incisors. The results showed intermediate status of female-to-male transsexuals' teeth between the males and females, which may suggest a genetic basis of transsexualism.

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Statistical Analysis of Designed Experiments, Third Edition

Cited by 64 publications

References 0 publications

Iterative Contextual Recurrent Classification of Chromosomes

Iterative Contextual Recurrent Classification of Chromosomes

Multimodal Emotion Recognition Using Deep Networks

The Metric Features of Teeth in Female-to-Male Transsexuals

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