Analysis and comparison of similarity measures for validation of generative algorithms in the context of probability density functions

Lingua: inglese

Editore: Cuvillier Jun 2021, 2021

373697454X / 9783736974548

Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

Venditore con 5 stelle

Venditore AbeBooks dal 11 gennaio 2012

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EUR 29,88

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Descrizione dell’articolo da parte del venditore

This item is printed on demand - it takes 3-4 days longer - Neuware -About 3700 people die in traffic accidents every day. Human error is the number one cause of accidents. Autonomous driving can greatly reduce the occurrence of traffic accidents. To release self-driving cars for road traffic, the system including software must be validated and tested efficiently. However, due to their criticality, the amount of data corresponding to safety-critical driving scenarios are limited. These driving scenes can be expressed as a time series. They represent the corresponding movement of the vehicle, including time vector, position coordinates, speed and acceleration. Such data can be provided on different ways. For example, in the form of a kinematic model. Alternatively, artificial intelligence or machine learning methods can be used. They have been widely used in the development of autonomous vehicles. For example, generative algorithms can be used to generate such safety-critical driving data. However, the validation of generative algorithms is a challenge in general. In most cases, their quality is assessed by means of expert knowledge (qualitative). In order to achieve a higher degree of automation, a quantitative validation approach is necessary. Generative algorithms are based on probability distributions or probability density functions. Accordingly, similarity measures can be used to evaluate generative algorithms. In this publication, such similarity measures are described and compared on the basis of defined evaluation criteria. With respect to the use case mentioned, a recommended similarity measure is implemented and validated for an example of a typical safety-critical driving scenario. 24 pp. Englisch.…

Codice articolo 9783736974548

Dati bibliografici

Titolo
Analysis and comparison of similarity measures for validation of generative algorithms in the context of probability density functions
Autore
Nico Schick
Editore
Cuvillier Jun 2021
Anno di pubblicazione
2021
Condizione
Neu
Rilegatura
Taschenbuch
Lingua
inglese
ISBN 10
373697454X
ISBN 13
9783736974548
Peso dell'articolo
47 grammi
Dimensioni
210x148x2 mm

BuchWeltWeit Ludwig Meier e.K.

Bergisch Gladbach, Germania

Venditore con 5 stelle

Venditore AbeBooks dal 11 gennaio 2012

Tariffe di spedizione da Germania a U.S.A.

ArticoloDa 5 a 15 giorni lavorativiDa 5 a 15 giorni lavorativi
Primo articoloEUR 23,00EUR 23,00
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BuchWeltWeit Ludwig Meier e.K.

Germania