MedNet: Medical deepfakes detection using an improved deep learning approach-Reference-Cited by-同舟云学术

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MedNet: Medical deepfakes detection using an improved deep learning approach

Published:2023-11-02 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Albahli Saleh,Nawaz Marriam

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-17562-5.pdf

Reference43 articles.

1. Sera T (2021) Computed tomography. Transparency in Biology. Springer, pp 167–187

2. Beek C (2018) Mcafee researchers find poor security exposes medical data to cybercriminals. McAfee Blogs

3. Nawaz M, Javed A, Irtaza A (2022) ResNet-Swish-Dense54: a deep learning approach for deepfakes detection. Visual Comput 1–22

4. Nawaz M, Javed A, Irtaza A (2023) Convolutional long short-term memory-based approach for deepfakes detection from videos. Multimed Tools Appl 1–24

5. School HM (2020) Radiation risk from medical imaging. Harvard Health Publishing. Available: https://www.health.harvard.edu/cancer/radiation-risk-from-medical-imaging. Accessed 2 Feb 2023

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Deep Learning Model for Detecting Fake Medical Images to Mitigate Financial Insurance Fraud;Computation;2024-08-29

2. A New Approach for Effective Medical Deepfake Detection in Medical Images;IEEE Access;2024

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