385 research outputs found

    An Image-Based Measure for Evaluation of Mathematical Expression Recognition

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    The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-38628-2_81Mathematical expression recognition is an active research field that is related to document image analysis and typesetting. In this study, we present a novel global performance evaluation measure for mathematical expression recognition based on image matching. Using an image representation for evaluation tries to overcome the representation ambiguity as human beings do. The results of a recent competition were used to perform several experiments in order to analyze the benefits and drawbacks of this measure.This work was partially supported by the Spanish MEC under the STraDA research project (TIN2012-37475-C02-01), the MITTRAL (TIN2009-14633-C03-01) project, the FPU grant (AP2009-4363), by the Generalitat Valenciana under the grant Prometeo/2009/014, and through the EU 7th Framework Programme grant tranScriptorium (Ref: 600707)Álvaro Muñoz, F.; Sánchez Peiró, JA.; Benedí Ruiz, JM. (2013). An Image-Based Measure for Evaluation of Mathematical Expression Recognition. En Pattern Recognition and Image Analysis. Springer. 682-690. https://doi.org/10.1007/978-3-642-38628-2_81S682690Álvaro, F., Sánchez, J.A., Benedí, J.M.: Unbiased evaluation of handwritten mathematical expression recognition. In: Proceedings of ICFHR, Italy, pp. 181–186 (2012)Chan, K.F., Yeung, D.Y.: Error detection, error correction and performance evaluation in on-line mathematical expression recognition. Pattern Recognition 34(8), 1671–1684 (2001)Chou, P.A.: Recognition of equations using a two-dimensional stochastic context-free grammar. In: Pearlman, W.A. (ed.) Visual Communications and Image Processing IV. SPIE Proceedings Series, vol. 1199, pp. 852–863 (1989)Garain, U., Chaudhuri, B.B.: A corpus for OCR research on mathematical expressions. Int. Journal on Document Analysis and Recognition 7, 241–259 (2005)Keysers, D., Deselaers, T., Gollan, C., Ney, H.: Deformation models for image recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence 29(8), 1422–1435 (2007)Mouchére, H., Viard-Gaudin, C., Garain, U., Kim, D.H., Kim, J.H.: ICFHR 2012 – Competition on Recognition of On-line Mathematical Expressions (CROHME 2012). In: Proceedings of ICFHR, Italy, pp. 807–812 (2012)Otsu, N.: A Threshold Selection Method from Gray-level Histograms. IEEE Transactions on Systems, Man and Cybernetics 9(1), 62–66 (1979)Sain, K., Dasgupta, A., Garain, U.: EMERS: a tree matching-based performance evaluation of mathematical expression recognition system. International Journal of Document Analysis and Recognition (2010)Toselli, A.H., Juan, A., Vidal, E.: Spontaneous Handwriting Recognition and Classification. In: Proceedings of ICPR, England, UK, pp. 433–436 (2004)Zanibbi, R., Blostein, D., Cordy, J.R.: Recognizing mathematical expressions using tree transformation. IEEE Trans. on Pattern Analysis and Machine Intelligence 24(11), 1–13 (2002)Zanibbi, R., Pillay, A., Mouchere, H., Viard-Gaudin, C., Blostein, D.: Stroke-based performance metrics for handwritten mathematical expressions. In: Proceedings of ICDAR, pp. 334–338 (2011

    A new crack tip element for the phantom-node method with arbitrary cohesive cracks

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    We have developed a new crack tip element for the phantom-node method. In this method, a crack tip can be placed inside an element. Therefore, cracks can propagate almost independent of the finite element mesh. We developed two different formulations for the three-node triangular element and fournode quadrilateral element, respectively. Although this method is well suited for the one-point quadrature scheme, it can be used with other general quadrature schemes. We provide some numerical examples for some static and dynamic problems

    Testing Simulation Theory with Cross-Modal Multivariate Classification of fMRI Data

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    The discovery of mirror neurons has suggested a potential neural basis for simulation and common coding theories of action perception, theories which propose that we understand other people's actions because perceiving their actions activates some of our neurons in much the same way as when we perform the actions. We propose testing this model directly in humans with functional magnetic resonance imaging (fMRI) by means of cross-modal classification. Cross-modal classification evaluates whether a classifier that has learned to separate stimuli in the sensory domain can also separate the stimuli in the motor domain. Successful classification provides support for simulation theories because it means that the fMRI signal, and presumably brain activity, is similar when perceiving and performing actions. In this paper we demonstrate the feasibility of the technique by showing that classifiers which have learned to discriminate whether a participant heard a hand or a mouth action, based on the activity patterns in the premotor cortex, can also determine, without additional training, whether the participant executed a hand or mouth action. This provides direct evidence that, while perceiving others' actions, (1) the pattern of activity in premotor voxels with sensory properties is a significant source of information regarding the nature of these actions, and (2) that this information shares a common code with motor execution

    An SVM Confidence-Based Approach to Medical Image Annotation

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    This paper presents the algorithms and results of the “idiap” team participation to the ImageCLEFmed annotation task in 2008. On the basis of our successful experience in 2007 we decided to integrate two different local structural and textural descriptors. Cues are com- bined through concatenation of feature vectors and through the Multi- Cue Kernel. The challenge this year was to annotate images coming mainly from classes with only few training examples. We tackled the problem on two fronts: (1) we introduced a further integration strategy using SVM as an opinion maker; (2) we enriched the poorly populated classes adding virtual examples. We submitted several runs considering different combinations of the proposed techniques. The run jointly using the feature concatenation, the confidence-based opinion fusion and the virtual examples ranked first among all submissions

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    Приведены рефераты статей данного номера на английском языке

    You turn me cold: evidence for temperature contagion

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    Introduction During social interactions, our own physiological responses influence those of others. Synchronization of physiological (and behavioural) responses can facilitate emotional understanding and group coherence through inter-subjectivity. Here we investigate if observing cues indicating a change in another's body temperature results in a corresponding temperature change in the observer. Methods Thirty-six healthy participants (age; 22.9±3.1 yrs) each observed, then rated, eight purpose-made videos (3 min duration) that depicted actors with either their right or left hand in visibly warm (warm videos) or cold water (cold videos). Four control videos with the actors' hand in front of the water were also shown. Temperature of participant observers' right and left hands was concurrently measured using a thermistor within a Wheatstone bridge with a theoretical temperature sensitivity of <0.0001°C. Temperature data were analysed in a repeated measures ANOVA (temperature × actor's hand × observer's hand). Results Participants rated the videos showing hands immersed in cold water as being significantly cooler than hands immersed in warm water, F(1,34) = 256.67, p0.1). There was however no evidence of left-right mirroring of these temperature effects p>0.1). Sensitivity to temperature contagion was also predicted by inter-individual differences in self-report empathy. Conclusions We illustrate physiological contagion of temperature in healthy individuals, suggesting that empathetic understanding for primary low-level physiological challenges (as well as more complex emotions) are grounded in somatic simulation

    On the reciprocal interaction between believing and feeling: an adaptive agent modelling perspective

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    An agent’s beliefs usually depend on informational or cognitive factors such as observation or received communication or reasoning, but also affective factors may play a role. In this paper, by adopting neurological theories on the role of emotions and feelings, an agent model is introduced incorporating the interaction between cognitive and affective factors in believing. The model describes how the strength of a belief may not only depend on information obtained, but also on the emotional responses on the belief. For feeling emotions a recursive body loop between preparations for emotional responses and feelings is assumed. The model introduces a second feedback loop for the interaction between feeling and belief. The strength of a belief and of the feeling both result from the converging dynamic pattern modelled by the combination of the two loops. For some specific cases it is described, for example, how for certain personal characteristics an optimistic world view is generated in the agent’s beliefs, or, for other characteristics, a pessimistic world view. Moreover, the paper shows how such affective effects on beliefs can emerge and become stronger over time due to experiences obtained. It is shown how based on Hebbian learning a connection from feeling to belief can develop. As these connections affect the strenghts of future beliefs, in this way an effect of judgment ‘by experience built up in the past’ or ‘by gut feeling’ can be obtained. Some example simulation results and a mathematical analysis of the equilibria are presented

    When a photograph can be heard: Vision activates the auditory cortex within 110 ms

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    As the makers of silent movies knew well, it is not necessary to provide an actual auditory stimulus to activate the sensation of sounds typically associated with what we are viewing. Thus, you could almost hear the neigh of Rodolfo Valentino's horse, even though the film was mute. Evidence is provided that the mere sight of a photograph associated with a sound can activate the associative auditory cortex. High-density ERPs were recorded in 15 participants while they viewed hundreds of perceptually matched images that were associated (or not) with a given sound. Sound stimuli were discriminated from non-sound stimuli as early as 110 ms. SwLORETA reconstructions showed common activation of ventral stream areas for both types of stimuli and of the associative temporal cortex, at the earliest stage, only for sound stimuli. The primary auditory cortex (BA41) was also activated by sound images after ∼ 200 ms

    Effectiveness of GenoType MTBDRsl in excluding TB drug resistance in a clinical trial

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    OBJECTIVES: To assess the performance of the GenoType MTBDRsl v1, a line-probe assay (LPA), to exclude baseline resistance to fluoroquinolones (FQs) and second-line injectables (SLIs) in the Standard Treatment Regimen of Anti-tuberculosis Drugs for Patients With MDR-TB 1 (STREAM 1) trial. METHODS: Direct sputum MTBDRsl results in the site laboratories were compared to indirect phenotypic drug susceptibility testing (pDST) results in the central laboratory, with DNA sequencing as a reference standard. RESULTS: Of 413 multidrug-resistant TB (MDR-TB) patients tested using MTBDRsl and pDST, 389 (94.2%) were FQ-susceptible and 7 (1.7%) FQ-resistant, while 17 (4.1%) had an inconclusive MTBDRsl result. For SLI, 372 (90.1%) were susceptible, 5 (1.2%) resistant and 36 (8.7%) inconclusive. There were 9 (2.3%) FQ discordant pDST/MTBDRsl results, of which 3 revealed a mutation and 5 (1.3%) SLI discordant pDST/MTBDRsl results, none of which were mutants on sequencing. Among the 17 FQ- and SLI MTBDRsl-inconclusive samples, sequencing showed 1 FQ- and zero SLI-resistant results, similar to frequencies among the conclusive MTBDRsl. The majority of inconclusive MTBDRsl results were associated with low bacillary load samples (acid-fast bacilli smear-negative or scantily positive) compared to conclusive results (P < 0.001). CONCLUSION: MTBDRsl can facilitate the rapid exclusion of FQ and SLI resistances for enrolment in clinical trials

    Skin Conductance Response to the Pain of Others Predicts Later Costly Helping

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    People show autonomic responses when they empathize with the suffering of another person. However, little is known about how these autonomic changes are related to prosocial behavior. We measured skin conductance responses (SCRs) and affect ratings in participants while either receiving painful stimulation themselves, or observing pain being inflicted on another person. In a later session, they could prevent the infliction of pain in the other by choosing to endure pain themselves. Our results show that the strength of empathy-related vicarious skin conductance responses predicts later costly helping. Moreover, the higher the match between SCR magnitudes during the observation of pain in others and SCR magnitude during self pain, the more likely a person is to engage in costly helping. We conclude that prosocial motivation is fostered by the strength of the vicarious autonomic response as well as its match with first-hand autonomic experience
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