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Author |
Enric Marti; Jordi Vitria; Alberto Sanfeliu |
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Title |
Reconocimiento de Formas y Análisis de Imágenes |
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Book Whole |
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Year |
1998 |
Publication |
Asociación Española de Reconocimientos de Formas y Análisis de Imágenes |
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Abstract |
Los sistemas actuales de reconocimiento automático del lenguaje oral se basan en dos etapas básicas de procesado: la parametrización, que extrae la evolución temporal de los parámetros que caracterizan la voz, y el reconocimiento propiamente dicho, que identifica la cadena de palabras de la elocución recibida con ayuda de los modelos que representan el conocimiento adquirido en la etapa de aprendizaje. Tomando como línea divisoria la palabra, dichos modelos son de tipo acústicofonético o gramatical. Los primeros caracterizan las palabras incluidas en el vocabulario de la aplicación o tarea a la que está orientado el sistema de reconocimiento, usando a menudo para ello modelos de unidades de habla de extensión inferior a la palabra, es decir, de unidades subléxicas. Por otro lado, la gramática incluye el conocimiento acerca de las combinaciones permitidas de palabras para formar las frases o su probabilidad. Queda fuera del esquema la denominada comprensión del habla, que utiliza adicionalmente el conocimiento semántico y pragmático para captar el significado de la elocución de entrada al sistema a partir de la cadena (o cadenas alternativas) de palabras que suministra el reconocedor. |
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AERFAI |
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ISBN |
84–922529–4–4 |
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Notes |
IAM;OR;MV |
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no |
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Call Number |
IAM @ iam @ MVS1998 |
Serial |
1620 |
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Author |
Ole Vilhelm-Larsen; Petia Radeva; Enric Marti |
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Title |
Guidelines for choosing optimal parameters of elasticity for snakes |
Type |
Book Chapter |
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Year |
1995 |
Publication |
Computer Analysis Of Images And Patterns |
Abbreviated Journal |
LNCS |
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Volume |
970 |
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Pages |
106-113 |
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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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Lecture Notes in Computer Science |
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LNCS |
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Notes |
MILAB;IAM |
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Call Number |
IAM @ iam @ LRM1995b |
Serial |
1558 |
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Author |
Carles Sanchez;F. Javier Sanchez; Antoni Rosell; Debora Gil |
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Title |
An illumination model of the trachea appearance in videobronchoscopy images |
Type |
Book Chapter |
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Year |
2012 |
Publication |
Image Analysis and Recognition |
Abbreviated Journal |
LNCS |
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Volume |
7325 |
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Pages |
313-320 |
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Keywords |
Bronchoscopy, tracheal ring, stenosis assesment, trachea appearance model, segmentation |
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Abstract |
Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways. This imaging modality provides realistic images and allows non-invasive minimal intervention procedures. Tracheal procedures are routinary interventions that require assessment of the percentage of obstructed pathway for injury (stenosis) detection. Visual assessment in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error.
This paper introduces an automatic method for the estimation of steneosed trachea percentage reduction in videobronchoscopic images. We look for tracheal rings , whose deformation determines the degree of obstruction. For ring extraction , we present a ring detector based on an illumination and appearance model. This model allows us to parametrise the ring detection. Finally, we can infer optimal estimation parameters for any video resolution. |
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Address |
Aveiro, Portugal |
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Springer Berlin Heidelberg |
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Lecture Notes in Computer Science |
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LNCS |
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ISSN |
0302-9743 |
ISBN |
978-3-642-31297-7 |
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800 |
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ICIAR |
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Notes |
MV;IAM |
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Call Number |
IAM @ iam @ SSR2012 |
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1898 |
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Author |
Fernando Vilariño; Debora Gil; Petia Radeva |
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Title |
A Novel FLDA Formulation for Numerical Stability Analysis |
Type |
Book Chapter |
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Year |
2004 |
Publication |
Recent Advances in Artificial Intelligence Research and Development |
Abbreviated Journal |
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Volume |
113 |
Issue |
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Pages |
77-84 |
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Keywords |
Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision |
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Abstract |
Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision. |
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Publisher |
IOS Press |
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Editor |
J. Vitrià, P. Radeva and I. Aguiló |
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ISBN |
978-1-58603-466-5 |
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Notes |
MV;IAM;MILAB;SIAI |
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Call Number |
IAM @ iam @ VGR2004 |
Serial |
1663 |
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Permanent link to this record |