H.5. Image Processing and Computer Vision
1. 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 , Spring 2020, , Pages 289-301

Abstract
  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.5. Image Processing and Computer Vision
2. Pedestrian Detection in Infrared Outdoor Images Based on Atmospheric Situation Estimation

Seyed M. Ghazali; Y. Baleghi

Volume 7, Issue 1 , Winter 2019, , Pages 1-16

Abstract
  Observation in absolute darkness and daytime under every atmospheric situation is one of the advantages of thermal imaging systems. In spite of increasing trend of using these systems, there are still lots of difficulties in analysing thermal images due to the variable features of pedestrians and atmospheric ...  Read More

H.3.15.2. Computational neuroscience
3. An Emotion Recognition Approach based on Wavelet Transform and Second-Order Difference Plot of ECG

A. Goshvarpour; A. Abbasi; A. Goshvarpour

Volume 5, Issue 2 , Summer 2017, , Pages 211-221

Abstract
  Emotion, as a psychophysiological state, plays an important role in human communications and daily life. Emotion studies related to the physiological signals are recently the subject of many researches. In This study a hybrid feature based approach was proposed to examine affective states. To this effect, ...  Read More

H.6. Pattern Recognition
4. Classification of ECG signals using Hermite functions and MLP neural networks

A. Ebrahimzadeh; M. Ahmadi; M. Safarnejad

Volume 4, Issue 1 , Winter 2016, , Pages 55-65

Abstract
  Classification of heart arrhythmia is an important step in developing devices for monitoring the health of individuals. This paper proposes a three module system for classification of electrocardiogram (ECG) beats. These modules are: denoising module, feature extraction module and a classification module. ...  Read More

5. High impedance fault detection: Discrete wavelet transform and fuzzy function approximation

M. Banejad; H. Ijadi

Volume 2, Issue 2 , Summer 2014, , Pages 149-158

Abstract
  This paper presets a method including a combination of the wavelet transform and fuzzy function approximation (FFA) for high impedance fault (HIF) detection in distribution electricity network. Discrete wavelet transform (DWT) has been used in this paper as a tool for signal analysis. With studying different ...  Read More