Image interpolation with adaptive k ‐nearest neighbours search and random non‐linear regression
نویسندگان
چکیده
منابع مشابه
Presentation of K Nearest Neighbor Gaussian Interpolation and comparing it with Fuzzy Interpolation in Speech Recognition
Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...
متن کاملRegression Conformal Prediction with Nearest Neighbours
In this paper we apply Conformal Prediction (CP) to the k -Nearest Neighbours Regression (k -NNR) algorithm and propose ways of extending the typical nonconformity measure used for regression so far. Unlike traditional regression methods which produce point predictions, Conformal Predictors output predictive regions that satisfy a given confidence level. The regions produced by any Conformal Pr...
متن کاملPresentation of K Nearest Neighbor Gaussian Interpolation and comparing it with Fuzzy Interpolation in Speech Recognition
Hidden Markov Model is a popular statisical method that is used in continious and discrete speech recognition. The probability density function of observation vectors in each state is estimated with discrete density or continious density modeling. The performance (in correct word recognition rate) of continious density is higher than discrete density HMM, but its computation complexity is very ...
متن کاملNearest Neighbours Search Using the PM-Tree
We introduce a method of searching the k nearest neighbours (k-NN) using PM-tree. The PM-tree is a metric access method for similarity search in large multimedia databases. As an extension of M-tree, the structure of PM-tree exploits local dynamic pivots (like M-tree does it) as well as global static pivots (used by LAESA-like methods). While in M-tree a metric region is represented by a hyper-...
متن کاملAn Adaptable k -Nearest Neighbors Algorithm for MMSE Image Interpolation
We propose an image interpolation algorithm that is nonparametric and learning-based, primarily using an adaptive k-nearest neighbor algorithm with global considerations through Markov random fields. The empirical nature of the proposed algorithm ensures image results that are data-driven and, hence, reflect "real-world" images well, given enough training data. The proposed algorithm operates o...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IET Image Processing
سال: 2020
ISSN: 1751-9667,1751-9667
DOI: 10.1049/iet-ipr.2019.1591