A Hybridization Method of Prototype Generation and Prototype Selection for K-NN rule Based on GSA

M. Rezaei; H. Nezamabadi-pour

Volume 10, Issue 2 , April 2022, , Pages 257-268


  The present study aims to overcome some defects of the K-nearest neighbor (K-NN) rule. Two important data preprocessing methods to elevate the K-NN rule are prototype selection (PS) and prototype generation (PG) techniques. Often the advantage of these techniques is investigated separately. In this paper, ...  Read More

H.5. Image Processing and Computer Vision
Statistical Wavelet-based Image Denoising using Scale Mixture of Normal Distributions with Adaptive Parameter Estimation

M. Saeedzarandi; H. Nezamabadi-pour; S. Saryazdi

Volume 8, Issue 2 , April 2020, , Pages 289-301


  Removing noise from images is a challenging problem in digital image processing. This paper presents an image denoising method based on a maximum a posteriori (MAP) density function estimator, which is implemented in the wavelet domain because of its energy compaction property. The performance of the ...  Read More

H.6.3.2. Feature evaluation and selection
MLIFT: Enhancing Multi-label Classifier with Ensemble Feature Selection

Sh kashef; H. Nezamabadi-pour

Volume 7, Issue 3 , July 2019, , Pages 355-365


  Multi-label classification has gained significant attention during recent years, due to the increasing number of modern applications associated with multi-label data. Despite its short life, different approaches have been presented to solve the task of multi-label classification. LIFT is a multi-label ...  Read More