Voice Activity Detection using Clustering-based Method in Spectro-Temporal Features Space

N. Esfandian; F. Jahani bahnamiri; S. Mavaddati

Volume 10, Issue 3 , July 2022, , Pages 401-409

https://doi.org/10.22044/jadm.2022.11439.2304

Abstract
  This paper proposes a novel method for voice activity detection based on clustering in spectro-temporal domain. In the proposed algorithms, auditory model is used to extract the spectro-temporal features. Gaussian Mixture Model and WK-means clustering methods are used to decrease dimensions of the spectro-temporal ...  Read More

Rice Classification with Fractal-based Features based on Sparse Structured Principal Component Analysis and Gaussian Mixture Model

S. Mavaddati; S. Mavaddati

Volume 9, Issue 2 , April 2021, , Pages 235-244

https://doi.org/10.22044/jadm.2021.9583.2090

Abstract
  Development of an automatic system to classify the type of rice grains is an interesting research area in the scientific fields associated with modern agriculture. In recent years, different techniques are employed to identify the types of various agricultural products. Also, different color-based and ...  Read More

H.5. Image Processing and Computer Vision
Sparse Structured Principal Component Analysis and Model Learning for Classification and Quality Detection of Rice Grains

S. Mavaddati

Volume 8, Issue 2 , April 2020, , Pages 161-175

https://doi.org/10.22044/jadm.2019.7402.1877

Abstract
  In scientific and commercial fields associated with modern agriculture, the categorization of different rice types and determination of its quality is very important. Various image processing algorithms are applied in recent years to detect different agricultural products. The problem of rice classification ...  Read More

H.5. Image Processing and Computer Vision
A Novel Face Detection Method Based on Over-complete Incoherent Dictionary Learning

S. Mavaddati

Volume 7, Issue 2 , April 2019, , Pages 263-278

https://doi.org/10.22044/jadm.2019.7215.1857

Abstract
  In this paper, face detection problem is considered using the concepts of compressive sensing technique. This technique includes dictionary learning procedure and sparse coding method to represent the structural content of input images. In the proposed method, dictionaries are learned in such a way that ...  Read More