A Gaussian mixture model based combined resampling algorithm for classification of imbalanced credit data sets

2019 ◽  
Vol 10 (12) ◽  
pp. 3687-3699 ◽  
Author(s):  
Xu Han ◽  
Runbang Cui ◽  
Yanfei Lan ◽  
Yanzhe Kang ◽  
Jiang Deng ◽  
...  
Keyword(s):  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture ◽  
Data Sets ◽  
Model Based ◽  
Credit Data

Classification of Chinese Popular Songs Using a Fusion Scheme of GMM Model Estimate and Formant Feature Analysis

2013 ◽  
Vol 479-480 ◽  
pp. 1006-1009
Author(s):  
Ing Jr Ding ◽  
Chih Ta Yen ◽  
Che Wei Chang
Keyword(s):  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture ◽  
Feature Analysis ◽  
Model Estimate ◽  
Model Based ◽  
Popular Songs ◽  
Feature Based ◽  
Fusion Scheme

In this paper, a fusion scheme that combines Gaussian mixture model (GMM) calculations and formant feature analysis, called GMM-Formant, is proposed for classification of Chinese popular songs. Generally, automatic classification of popular music could be performed by two main categories of techniques, model-based and feature-based approaches. In model-based classification techniques, GMM is widely used for its simplicity. In feature-based music recognition, the formant parameter is an important acoustic feature for evaluation. The proposed GMM-Formant method takes use of linear interpolation for combining GMM likelihood estimates and formant evaluation results appropriately. GMM-Formant will effectively adjust the likelihood score, which is derived from GMM calculations, by referring to certain degree of formant feature evaluation outcomes. By considering both model-based and feature-based techniques for song classification, GMM-Formant provides a more reliable recognition classification result and therefore will maintain a satisfactory performance in recognition accuracy. Experimental results obtained from a musical data set of numerous Chinese popular songs show the superiority of the proposed GMM-Formant. Keywords: Song classification; Gaussian mixture model; Formant feature; GMM-Formant.

scholarly journals Detection and Classification of Vehicles on Curved Roads

2019 ◽  
Vol 8 (10S) ◽  
pp. 152-156
Keyword(s):  
Object Detection ◽  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Gaussian Mixture ◽  
Traffic Monitoring ◽  
Moving Object Detection ◽  
Morphological Operations ◽  
Moving Vehicles ◽  
Blob Analysis

Detection of a vehicle is a very important aspect for traffic monitoring. It is based on the concept of moving object detection. Classifying the detected object as vehicle and class of vehicle is also having application in various application domains. This paper aims at providing an application of vehicle detection and classification concept to detect vehicles along curved roads in Indian scenarios. The main purpose is to ensure safety in such roads. Gaussian mixture model and blob analysis are the methods applied for the detection of vehicles. Morphological operations are used to eliminate noise. The moving vehicles are detected and the class of the vehicle is identified.

scholarly journals Massive MIMO Codebook Design Using Gaussian Mixture Model Based Clustering

2022 ◽  
Vol 32 (1) ◽  
pp. 361-375
Author(s):  
S. Markkandan ◽  
S. Sivasubramanian ◽  
Jaison Mulerikkal ◽  
Nazeer Shaik ◽  
Beulah Jackson ◽  
...  
Keyword(s):  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Massive Mimo ◽  
Gaussian Mixture ◽  
Model Based Clustering ◽  
Codebook Design ◽  
Model Based
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