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Please use this identifier to cite or link to this item: http://lrcdrs.bennett.edu.in:80/handle/123456789/4531
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dc.contributor.authorBadotra, Sumit
dc.contributor.authorGoyal, Ankush
dc.contributor.authorKumar, Arun
dc.contributor.authorTyagi, Akshat
dc.date.accessioned2024-05-30T11:37:51Z-
dc.date.available2024-05-30T11:37:51Z-
dc.date.issued2023
dc.identifier.issn978-93-5053-903-3
dc.identifier.urihttp://lrcdrs.bennett.edu.in:80/handle/123456789/4531-
dc.description.abstractSpoofing attacks, where adversaries attempt to deceive biometric systems by using false biometric characteristics, pose a significant threat to the security of video-based biometric systems. Antispoofing techniques aim to detect and prevent these attacks by distinguishing between genuine and fake biometric features. In recent years, multifeature fusion-based approaches have gained attention due to their ability to combine information from multiple sources, leading to improved performance. This research paper presents an overview of anti-spoofing techniques in video-based biometric systems with a focus on multi- functional fusion approaches. The paper summarizes the challenges associated with spoofing attacks, discusses the various features that can be obtained from videos for anti-spoofing, and presents various fusion strategies for combining these features. Furthermore, the article discusses the advantages and limitations of multifunctional fusion approaches and highlights current research trends and future directions in this field.en_US
dc.publisherCyber Tech Publicationsen_US
dc.titleDemand for Bike Sharingen_US
dc.typeBook Chapteren_US
Appears in Collections:Book Chapters_ SCSET

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