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Hans Stadthagen-Gonzalez, Luis Lopez, M. Carmen Parafita, & C. Alejandro Parraga. (2018). Using two-alternative forced choice tasks and Thurstone law of comparative judgments for code-switching research. In Linguistic Approaches to Bilingualism (pp. 67–97).
Abstract: This article argues that 2-alternative forced choice tasks and Thurstone’s law of comparative judgments (Thurstone, 1927) are well suited to investigate code-switching competence by means of acceptability judgments. We compare this method with commonly used Likert scale judgments and find that the 2-alternative forced choice task provides granular details that remain invisible in a Likert scale experiment. In order to compare and contrast both methods, we examined the syntactic phenomenon usually referred to as the Adjacency Condition (AC) (apud Stowell, 1981), which imposes a condition of adjacency between verb and object. Our interest in the AC comes from the fact that it is a subtle feature of English grammar which is absent in Spanish, and this provides an excellent springboard to create minimal code-switched pairs that allow us to formulate a clear research question that can be tested using both methods.
Keywords: two-alternative forced choice and Thurstone's law; acceptability judgment; code-switching
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Veronica Romero, Alicia Fornes, Enrique Vidal, & Joan Andreu Sanchez. (2016). Using the MGGI Methodology for Category-based Language Modeling in Handwritten Marriage Licenses Books. In 15th international conference on Frontiers in Handwriting Recognition.
Abstract: Handwritten marriage licenses books have been used for centuries by ecclesiastical and secular institutions to register marriages. The information contained in these historical documents is useful for demography studies and
genealogical research, among others. Despite the generally simple structure of the text in these documents, automatic transcription and semantic information extraction is difficult due to the distinct and evolutionary vocabulary, which is composed mainly of proper names that change along the time. In previous
works we studied the use of category-based language models to both improve the automatic transcription accuracy and make easier the extraction of semantic information. Here we analyze the main causes of the semantic errors observed in previous results and apply a Grammatical Inference technique known as MGGI to improve the semantic accuracy of the language model obtained. Using this language model, full handwritten text recognition experiments have been carried out, with results supporting the interest of the proposed approach.
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Alex Goldhoorn, Arnau Ramisa, Ramon Lopez de Mantaras, & Ricardo Toledo. (2007). Using the Average Landmark Vector Method for Robot Homing. In Artificial Intelligence Research and Development, Proceedings of the 10th International Conference of the ACIA (Vol. 163, 331–338).
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David Roche, Debora Gil, & Jesus Giraldo. (2011). Using statistical inference for designing termination conditions ensuring convergence of Evolutionary Algorithms. In 11th European Conference on Artificial Life.
Abstract: A main challenge in Evolutionary Algorithms (EAs) is determining a termination condition ensuring stabilization close to the optimum in real-world applications. Although for known test functions distribution-based quantities are good candidates (as far as suitable parameters are used), in real-world problems an open question still remains unsolved. How can we estimate an upper-bound for the termination condition value ensuring a given accuracy for the (unknown) EA solution?
We claim that the termination problem would be fully solved if we defined a quantity (depending only on the EA output) behaving like the solution accuracy. The open question would be, then, satisfactorily answered if we had a model relating both quantities, since accuracy could be predicted from the alternative quantity. We present a statistical inference framework addressing two topics: checking the correlation between the two quantities and defining a regression model for predicting (at a given confidence level) accuracy values from the EA output.
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Karla Lizbeth Caballero, Joel Barajas, & Petia Radeva. (2007). Using Reconstructed IVUS Images for Coronary Plaque Classification. In Engineering in Medicine and Biology Society, 29th Annual International Conference of the IEEE (2167–2170).
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Karla Lizbeth Caballero, Joel Barajas, Oriol Pujol, J. Mauri, & Petia Radeva. (2006). Using Radio Frequency Reconstructed IVUS Images in Tissue Classification.
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Jose A. Garcia, David Masip, Valerio Sbragaglia, & Jacopo Aguzzi. (2016). Using ORB, BoW and SVM to identificate and track tagged Norway lobster Nephrops Norvegicus (L.). In 3rd International Conference on Maritime Technology and Engineering.
Abstract: Sustainable capture policies of many species strongly depend on the understanding of their social behaviour. Nevertheless, the analysis of emergent behaviour in marine species poses several challenges. Usually animals are captured and observed in tanks, and their behaviour is inferred from their dynamics and interactions. Therefore, researchers must deal with thousands of hours of video data. Without loss of generality, this paper proposes a computer
vision approach to identify and track specific species, the Norway lobster, Nephrops norvegicus. We propose an identification scheme were animals are marked using black and white tags with a geometric shape in the center (holed
triangle, filled triangle, holed circle and filled circle). Using a massive labelled dataset; we extract local features based on the ORB descriptor. These features are a posteriori clustered, and we construct a Bag of Visual Words feature vector per animal. This approximation yields us invariance to rotation
and translation. A SVM classifier achieves generalization results above 99%. In a second contribution, we will make the code and training data publically available.
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Fernando Vilariño, & Dan Norton. (2017). Using mutimedia tools to spread poetry collections. In Internet librarian International Conference.
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J. Pladellorens, Joan Serrat, A. Castell, & M.J. Yzuel. (1993). Using mathematical morphology to determine left ventricular contours. Physics in Medicine and Biology., 1877––1894.
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A. Martinez, & Jordi Vitria. (1997). Using Low-Dimensional Spaces for Face Recognition..
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David Guillamet, & Jordi Vitria. (1999). Using Eigenspace analysis of color distributions for object recognition.
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X. Binefa, F. Javier Sanchez, F.X. Perez, Xavier Roca, Jordi Vitria, & Juan J. Villanueva. (1993). Using defocus in optical inspection of integrated circuits. In Institute of Physics Conferences Series (Vol. 135, pp. 389–392). Institute of Physics.
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Josep Llados, Horst Bunke, & Enric Marti. (1997). Using Cyclic String Matching to Find Rotational and Reflectional Symmetries in Shapes. In Intelligent Robots: Sensing, Modeling and Planning (pp. 164–179). World Scientific Press.
Abstract: Dagstuhl Workshop
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Josep Llados, Horst Bunke, & Enric Marti. (1996). Using cyclic string matching to find rotational and reflectional symmetric shapes. In H. B. H. N. R.C. Bolles (Ed.), Dagstuhl Seminar on Modelling and Planning for Sensor–based Intelligent Robot Systems. Saarbrucken (Germany).: World Scientific.
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M. Bressan, David Guillamet, & Jordi Vitria. (2000). Using an ICA representation of local color histograms for object recognition..
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