Une pure merveille !
Un roman d'une grande beauté, drôle, fin, extrêmement lumineux sur des sujets difficiles : la perte de
l'être aimé, la dureté de la vie et la tristesse qu'on barricade parfois... Elise franco-japonaise,
orpheline de sa maman veut poser LA question à son père et elle en trouvera le courage au fil des pages,
grâce au retour de sa grand-mère du japon, de sa rencontre avec son extravagante amie Stella..
Ensemble il ne diront plus Sayonara mais Mata Ne !
Two important subproblems of computer vision are the detection and recognition of 2D objects in gray-level images. This book discusses the construction...
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En librairie
Résumé
Two important subproblems of computer vision are the detection and recognition of 2D objects in gray-level images. This book discusses the construction and training of models, computational approaches to efficient implementation, and parallel implementations in biologically plausible neural network architectures. The approach is based on statistical modeling and estimation, with an emphasis on simplicity, transparency, and computational efficiency. The book describes a range of deformable template models, from coarse sparse models involving discrete, fast computations to more finely detailed models based on continuum formulations, involving intensive optimization. Each model is defined in terms of a subset of points on a reference grid (the template), a set of admissible instantiations of these points (deformations), and a statistical model for the data given a particular instantiation of the object present in the image. A recurring theme is a coarse-to-fine approach to the solution of vision problems. The book provides detailed descriptions of the algorithms used as well as the code, and the software and data sets are available on the Web.
Sommaire
Detection and Recognition : Overview of Models
1D Models : Deformable Contours
ID Models : Deformable Curves
2D Models : Deformable Images
Sparse Models : Formulation, Training, and Statistical Properties
Detection of Sparse Models : Dynamic Programming
Detection of Sparse Models : Counting
Object Recognition
Scene Analysis : Merging Detection and Recognition