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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..
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A. Martinez, & Jordi Vitria. (1995). Designing and Implementing Real Walking Agents using Virtual Environments.
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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.
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Jordi Vitria, & J. Llacer. (1995). Recovering brightness and depth from focus using the Expectation-Maximization Algorithm..
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D. Seron, F. Moreso, C. Gratin, & Jordi Vitria. (1995). Morphological Granulometries and Quantification of Interstitial Chronic Renal Damage.
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V. Valev, & Petia Radeva. (1995). ECG Recognition by Non-Reducible Descriptors..
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V. Valev, & Petia Radeva. (1995). Constructing Quantitative Non-Reducible Descriptors..
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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..
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J.R. Serra, S. Casadei, & J.B. Subirana. (1995). Non-Cartesian Networks for Middle Level Vision..
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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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