ENHANCING IMAGE SPAM DETECTIONAND DEEPFAKE VIDEO DETECTION WITH DEEP LEARNING TECHNIQUES

Abstract: The emergence of image spam and deepfake videos presents a new risk in the digital environment, creating a need for new detection frameworks that move beyond traditional frameworks. CapsuleVGG19 is a new framework to address these new risks by combining the strengths of Capsule Networks (CapsNets) and VGG19, which is a type of Convolutional Neural Networks (CNN). CapsNets are designed to learn hierarchical relationships in images allowing for a new approach to feature learning, and VGG19 .

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-17
DOI
https://doi.org/10.5281/zenodo.15680222
Primary Topic
Digital Media Forensic Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

ENHANCING IMAGE SPAM DETECTIONAND DEEPFAKE VIDEO DETECTION WITH DEEP LEARNING TECHNIQUES

Zenodo (CERN European Organization for Nuclear Research)
Digital Media Forensic Detection
article

ENHANCING IMAGE SPAM DETECTIONAND DEEPFAKE VIDEO DETECTION WITH DEEP LEARNING TECHNIQUES

article en

Abstract

Abstract: The emergence of image spam and deepfake videos presents a new risk in the digital environment, creating a need for new detection frameworks that move beyond traditional frameworks. CapsuleVGG19 is a new framework to address these new risks by combining the strengths of Capsule Networks (CapsNets) and VGG19, which is a type of Convolutional Neural Networks (CNN). CapsNets are designed to learn hierarchical relationships in images allowing for a new approach to feature learning, and VGG19 .

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 55%
Digital Media Forensic Detection
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ENHANCING IMAGE SPAM DETECTIONAND DEEPFAKE VIDEO DETECTION WITH DEEP LEARNING TECHNIQUES · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS