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Jordi Vitria, C. Gratin, D. Seron, & F. Moreso. (1995). Morphological image analysis for quantification of renal damage.
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Joan Serrat. (1995). Aplicacion del analisis de imagenes en radiologia. In VI National Simposium on Pattern Recognition and image Analysis.
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A. Martinez, & Jordi Vitria. (1995). A Development Plataform for Autonomous Agents. ASI–AA–95 – Practice and Future of Autonomous Agents., .
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A. Martinez, Jordi Vitria, & S. Sampayo. (1995). Atlas: a Hexapod driven by a Neural Network..
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Petia Radeva, & Enric Marti. (1995). Facial Features Segmentation by Model-Based Snakes..
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Antonio Lopez, & Joan Serrat. (1995). Image Analysis through Surface Geometric Descriptors. In VI National Simposium on Pattern Recognition and image Analysis..
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Jordi Vitria, & J. Llacer. (1995). Recovering brightness and depth from focus using the Expectation-Maximization Algorithm. In VI National Simposium on Pattern Recognition and image Analysis.
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D. Seron, F. Moreso, C. Gratin, & Jordi Vitria. (1995). Morphological Granulometries and Quantification of Interstitial Chronic Renal Damage. In VI National Simposium on Pattern Recognition and image Analysis..
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V. Valev, & Petia Radeva. (1995). ECG Recognition by Non-Reducible Descriptors. In Portuguese Conference on Pattern Recognition..
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V. Valev, & Petia Radeva. (1995). Constructing Quantitative Non-Reducible Descriptors. In 9th Scandinavian Conference on Artificial Intelligence (Vol. 2, pp. 981–988).
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C. Molina, & J.B. Subirana. (1995). Reduction of complexity for object recognition algorithms.
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C. Molina, & J.B. Subirana. (1995). Polynomial-Time Algorithm for 2D object recognition. In VI National Simposium on Pattern Recognition and image Analysis.
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J.R. Serra, S. Casadei, & J.B. Subirana. (1995). Non-Cartesian Networks for Middle Level Vision. In VI National Simposium on Pattern Recognition and image Analysis.
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Ole Vilhelm-Larsen, Petia Radeva, & Enric Marti. (1995). Guidelines for choosing optimal parameters of elasticity for snakes. In Computer Analysis Of Images And Patterns (Vol. 970, pp. 106–113). LNCS.
Abstract: This paper proposes a guidance in the process of choosing and using the parameters of elasticity of a snake in order to obtain a precise segmentation. A new two step procedure is defined based on upper and lower bounds on the parameters. Formulas, by which these bounds can be calculated for real images where parts of the contour may be missing, are presented. Experiments on segmentation of bone structures in X-ray images have verified the usefulness of the new procedure.
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Ole Larsen, Petia Radeva, & Enric Marti. (1995). Bounds on the optimal elasticity parameters for a snake. Image Analysis and Processing, , 37–42.
Abstract: This paper develops a formalism by which an estimate for the upper and lower bounds for the elasticity parameters for a snake can be obtained. Objects different in size and shape give rise to different bounds. The bounds can be obtained based on an analysis of the shape of the object of interest. Experiments on synthetic images show a good correlation between the estimated behaviour of the snake and the one actually observed. Experiments on real X-ray images show that the parameters for optimal segmentation lie within the estimated bounds.
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