Search results for "RECOGNITION"
showing 10 items of 3607 documents
Silhouette encoding and synthesis using elliptic Fourier descriptors, and applications to videoconferencing
2004
Abstract This paper investigates the use of elliptic Fourier descriptors as a shape descriptor for encoding the silhouette of a person. Shape descriptors are here used for predicting the shape of silhouettes in missing frames within a sequence. This prediction scheme is applied to the case of generating in-between images in a low frame rate videoconferencing system, where the reconstructed silhouette is used as a binary mask for reducing the computational time for the frame reconstruction.
Bot or Not? A Case Study on Bot Recognition from Web Session Logs
2019
This work reports on a study of web usage logs to verify whether it is possible to achieve good recognition rates in the task of distinguishing between human users and automated bots using computational intelligence techniques. Two problem statements are given, offline (for completed sessions) and on-line (for sequences of individual HTTP requests). The former is solved with several standard computational intelligence tools. For the second, a learning version of Wald’s sequential probability ratio test is used.
Bot or not? a case study on bot recognition from web session logs
2018
This work reports on a study of web usage logs to verify whether it is possible to achieve good recognition rates in the task of distinguishing between human users and automated bots using computational intelligence techniques. Two problem statements are given, offline (for completed sessions) and on-line (for sequences of individual HTTP requests). The former is solved with several standard computational intelligence tools. For the second, a learning version of Wald’s sequential probability ratio test is used.
Quantifying the complexity of short-term heart period variability through K nearest neighbor local linear prediction
2008
The complexity of short-term heart period (HP) variability was quantified exploiting the paradigm that associates the degree of unpredictability of a time series to its dynamical complexity. Complexity was assessed through k-nearest neighbor local linear prediction. A proper selection of the parameter k allowed us to perform either linear or nonlinear prediction, and the comparison of the two approaches to infer the presence of nonlinear dynamics. The method was validated on simulations reproducing linear and nonlinear time series with varying levels of predictability. It was then applied to HP variability series measured from healthy subjects during head-up tilt test, showing that short-te…
Experimental approach for testing the uncoupling between cardiovascular variability series
2002
In cardiovascular variability analysis, the significance of the coupling between two series is commonly assessed by defining a zero level on the magnitude-squared coherence (MSC). Although the use of the conventional value of 0.5 does not consider the dependence of MSC estimates on the analysis parameters, a theoretical threshold Tt is available only for the weighted covariance (WC) estimator. In this study, an experimental threshold for zero coherence Te was derived by a statistical test from the sampling distribution of MSC estimated on completely uncoupled time series. MSC was estimated by the WC method (Parzen window, spectral bandwidth B = 0.015, 0.02, 0.025, 0.03 Hz) and by the parame…
Information dynamics in cardiorespiratory time series during mental stress testing
2014
In this study, we assessed the information dynamics of respiration and heart rate variability during mental stress testing by means of the cross-entropy, a measure of cardiorespiratory coupling, and the self-entropy of the tachogram conditioned to the knowledge of respiration. Although stress is related to a reduction in vagal activity, no difference in cardiorespiratory coupling was found when 5 minutes of rest and stress were compared. The conditional self-entropy, on the other hand, showed significantly higher values during stress, indicating a higher predictability of the tachogram. These results show that entropy analyses of cardiorespiratory data reveal new information that could not …
Do serifs provide an advantage in the recognition of written words?
2011
A neglected issue in the literature on visual-word recognition is the careful examination of parameters such as font, size, or interletter/interword spacing on reading times. Here we analysed whether serifs (i.e., the small features at the end of strokes) play a role in lexical access. Traditionally, serif fonts have been considered easier to read than sans serif fonts, but prior empirical evidence is scarce and inconclusive. Here we conducted a lexical decision experiment (i.e., a word/nonword discrimination task) in which we compared words from the same family (Lucida) either with a serif font or with a sans serif font—in both a block list and a mixed list. Results showed a small, but sig…
A speech recognition approach for an industrial training station
2021
This paper presents a speech recognition service used in the context of commanding and guiding the activities around an industrial training station. The entire concept is built on a decentralized microservice architecture and one of the many hardware and software components is the speech recognition engine. This engine grants users the possibility to interact seamlessly with other components in order to ensure a gradual and productive learning process. By working with different API’s for both English and Romanian languages, the presented approach manages to obtain good speech recognition for defining task phrases aiding the training procedure and to reduce the recognition required time by a…
Solution Using Clustering Methods
1987
The main aim of this analysis is to find out typical morphologies from the multivariate and longitudinal data set on growing children and to describe the morphological evolution of the found groups of girls. The finding out of typical morphologies is, in our opinion, strictly linked to the search of structures in the individuals and in the variables.
Quantifying Mean Shape and Variability of Footprints Using Mean Sets
2005
This paper1 presents an application of several definitions of a mean set for use in footwear design. For a given size, footprint pressure images corresponding to different individuals constitute our raw data. Appropriate footwear design needs to have knowledge of some kind of typical footprint. Former methods based on contour relevant points are highly sensitive to contour noise; moreover, they lack repeatability because of the need for the intervention of human designers. The method proposed in this paper is based on using mean sets on the thresholded images of the pressure footprints. Three definitions are used, two of them from Vorob’ev and Baddeley-Molchanov and one morphological mean p…