•  Retrait gratuit dans votre magasin Club
  •  7.000.000 titres dans notre catalogue
  •  Payer en toute sécurité
  •  Toujours un magasin près de chez vous     
  •  Retrait gratuit dans votre magasin Club
  •  7.000.000 titres dans notre catalogue
  •  Payer en toute sécurité
  •  Toujours un magasin près de chez vous

Artificial Neural Networks for Computer Vision

Yi-Tong Zhou, Rama Chellappa
Livre broché | Anglais | Research Notes in Neural Computing | n° 5
83,95 €
+ 167 points
Livraison 2 à 3 semaines
Passer une commande en un clic
Payer en toute sécurité
Livraison en Belgique: 3,99 €
Livraison en magasin gratuite

Description

This monograph is an outgrowth of the authors' recent research on the de- velopment of algorithms for several low-level vision problems using artificial neural networks. Specific problems considered are static and motion stereo, computation of optical flow, and deblurring an image. From a mathematical point of view, these inverse problems are ill-posed according to Hadamard. Researchers in computer vision have taken the "regularization" approach to these problems, where one comes up with an appropriate energy or cost function and finds a minimum. Additional constraints such as smoothness, integrability of surfaces, and preservation of discontinuities are added to the cost function explicitly or implicitly. Depending on the nature of the inver- sion to be performed and the constraints, the cost function could exhibit several minima. Optimization of such nonconvex functions can be quite involved. Although progress has been made in making techniques such as simulated annealing computationally more reasonable, it is our view that one can often find satisfactory solutions using deterministic optimization algorithms.

Spécifications

Parties prenantes

Auteur(s) :
Editeur:

Contenu

Nombre de pages :
170
Langue:
Anglais
Collection :
Tome:
n° 5

Caractéristiques

EAN:
9780387976839
Date de parution :
23-12-91
Format:
Livre broché
Format numérique:
Trade paperback (VS)
Dimensions :
156 mm x 234 mm
Poids :
267 g

Les avis