Separability Assessment of Selected Types of Vehicle-Associated Noise

Kurowski, Adam; Marciniuk, Karolina; Kostek, Bożena

doi:10.1007/978-3-319-43982-2_10

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…By definition, it is a kind of graph, for which a new, neighboring top of the graph cannot be added. To obtain such a result, we used the Bron-Kebrosch recombination algorithm of, which finds the maximum clique of the graph [8].…”

Section: Methodsmentioning

confidence: 99%

“…To achieve this, Behrens-Fisher statistic was used, for which the critical value adopted in the study was 2.086. The combination of both algorithms enables to find parameters that may allow for effective classification of the tested vehicle types [8] as it guarantees an appropriate level of separation between classes. Optimized feature vector was used for training and testing SVMs.…”

Section: Methodsmentioning

confidence: 99%

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Support Vector Machine Applied to Road Traffic Event Classification

Blaszke

Kostek

2018

MATEC Web Conf.

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The aim of this paper is to present results of road traffic event signal recognition. First, several types of systems for road traffic monitoring, including Intelligent Transport System (ITS) are shortly described. Then, assumptions of creating a database of vehicle signals recorded in different weather and road conditions are outlined. Registered signals were edited as single vehicle pass by. Using the Matlab-based application a feature vector containing 48 parameters was extracted and analyzed in the context of parameter separability and classification effectiveness employing SVM (Support Vector Machine) algorithm. In conclusion, the classifier developed and its effectiveness were discussed.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Support Vector Machine Applied to Road Traffic Event Classification

Blaszke

Kostek

2018

MATEC Web Conf.

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“…Using the above scenario a few classification sessions were conducted utilizing the Support Vector Machine (SVM) method [13]. However, it should be mentioned that energy of the tire noise is cumulated near 1 kHz frequency.…”

Section: Vehicle Body Typementioning

confidence: 99%

Acoustic Road Monitoring

2018

Self Cite

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The subject of this research is showing the performance of an automatic acoustic road monitoring system proposed by the authors. The main goal of the study is describing road traffic by means of an acoustic representation and testing effectiveness of traffic flow sensors. Evaluation metrics of the road conditions such as velocity of the traffic flow, its structure and weather condition are presented along with acoustic descriptors derived from the audio signal analysis. Accuracy of emergency vehicles pass by detection based on acoustic monitoring is also briefly described.

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Intelligent Audio Signal Processing – Do We Still Need Annotated Datasets?

Kostek

2022

Intelligent Information and Database Systems

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Separability Assessment of Selected Types of Vehicle-Associated Noise

Cited by 5 publications

References 10 publications

Support Vector Machine Applied to Road Traffic Event Classification

Support Vector Machine Applied to Road Traffic Event Classification

Acoustic Road Monitoring

Intelligent Audio Signal Processing – Do We Still Need Annotated Datasets?

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