| The LNCS series reports state-of-the-art results in computer science research,development,and education,at a high level and in both printed and electronic form.Enjoying tight cooperation with the R&D community,with numerous individuals,as well as with prestigious organizations and societies,LNCS has grown into the most comprehensive computer science resarch forum available. The scope of LNCS,including its subseries LNAI,spans the whole range of computer science and information technology including interdisciplinary topics in a variety of application fields.The type of material publised traditionally includes. -proceedings(published in time for the respective conference) -post-proceedings(consisting of thoroughly revised final full papers) -research monographs(which may be basde on outstanding PhD work,research projects,technical reports,etc.). |
| image filtering, restoration and segmentation ultrasound image denoising by spatially varying frequency compounding exploiting low-level image segmentation for object recognition wavelet based noise reduction by identification of correlations template based gibbs probability distributions for texture modeling and segmentation etficient combination of probabilistic sampling approximations for robust hnage segmentation i)iffusion-like reconstruction schemes fi'om linear data models reduction of ring artifacts in high resolution x-ray microtomography hnages a probabilistic multi-phase model for variational hnage segmentation provably correct edgel linking and subpixel boundary reconstruction the edge preserving wiener filter for scalar and tensor valued images from adaptive averaging to accelerated nonlinear diffusion filtering introducing dynamic prior knowledge to partially-blurred image restoration shape analysis and representation on-line, incremental learning of a robust active shape model using irreducible group representations for invariant 3i) shape description shape matching by variational computation of geodesics on a manitbld a modification of the level set speed function to bridge gaps in data generation and initialization of stable 3d mass-spring models for the segmentation of the thyroid cartilage preserving topological information in the windowed hough transform for rectangle extraction .recognition, categorization and detection fast scalar and vectorial grayscale based invariant features tbr 3d cell nuclei localization and classification …… computer vision and lmage retrievel anuthor index |
内容加载中，请稍后...
商品评论（0条）