منابع مشابه
Polyline Simpliication Using Quadric Error Metric with Bounded Error Polyline Simpliication Using Quadric Error Metric with Bounded Error Polyline Simpliication Using Quadric Error Metric with Bounded Error
We study the problem of polygonal line simpliication. The objective is to seek a polygonal line of smaller size that approximates the original one well. We present an algorithm that is based on edge contraction. An edge contraction merges two adjacent vertices into a new vertex and this new vertex will be made the new endpoint of the uncontracted edges incident to the two vertices merged. Thus,...
متن کاملError Bounds and Metric Subregularity
Necessary and sufficient criteria for metric subregularity (or calmness) of set-valued mappings between general metric or Banach spaces are treated in the framework of the theory of error bounds for a special family of extended real-valued functions of two variables. A classification scheme for the general error bound and metric subregularity criteria is presented. The criteria are formulated i...
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هدف از انجام این تحقیق مشخص کردن موثرترین متد اصلاح خطا بر روی دقت آهنگ و تاکید تلفظ کلمه در زبان انگلیسی بود. این تحقیق با پیاده کردن چهار متد ارائه اصلاح خطا در چهار گروه، سه گروه آزمایشی و یک گروه تحت کنترل، انجام شد که گروه های فوق الذکر شامل دانشجویان سطح بالای متوسط کتاب اول passages بودند. گروه اول شامل 15، دوم 14، سوم 15 و آخرین 16 دانشجو بودند. دوره مربوطه به مدت 10 هفته ادامه یافت و د...
15 صفحه اولDiscrete Differential Error Metric for Surface Simplification
In this paper we propose a new discrete differential error metric for surface simplification. Many surface simplification algorithms have been developed in order to produce rapidly high quality approximations of polygonal models, and the quadric error metric based on the distance error is the most popular and successful error metric so far. Even though such distance based error metrics give vis...
متن کامل1 toward an Improved Error Metric
In many computer vision algorithms, the well known Euclidean or SSD (sum of the squared differences) metric is prevalent and justified from a maximum likelihood perspective when the additive noise is Gaussian. However, Gaussian noise distribution assumption is often invalid. Previous research has found that other metrics such as double exponential metric or Cauchy metric provide better results,...
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ژورنال
عنوان ژورنال: Science
سال: 1905
ISSN: 0036-8075,1095-9203
DOI: 10.1126/science.21.546.922