A Novel Approach to Image Forgery Detection Techniques in Real World Applications-Reference-Cited by-同舟云学术

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A Novel Approach to Image Forgery Detection Techniques in Real World Applications

Published:2022 Issue: Volume: Page:461-473
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
Short-container-title:

Author:

Patil Dhanishtha,Patil Kajal,Narawade Vaibhav

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-4831-2_38

Reference40 articles.

1. Sencar HT, Memon N (eds) (2013) digital image forensics. Springer-Verlag New York. https://doi.org/10.1007/978-1-4614-0757-7

2. Walia S, Kumar K (2018) Digital image forgery detection: a systematic scrutiny. Aust J Forensic Sci 51:1–39. https://doi.org/10.1080/00450618.2018.1424241

3. Kasban H, Nassar S (2020) An efficient approach for forgery detection in digital images using Hilbert Huang transform. Appl Soft Comput 97:106728. https://doi.org/10.1016/j.asoc.2020.106728

4. The 2015 IEEE RIVF International Conference on Computing. Communication Technologies Research, Innovation, and Vision for Future (RIVF)

5. Bharti CN, Tandel P (2016) A survey of image forgery detection techniques. In: International conference on wireless communications, signal processing and networking (WiSPNET). IEEE. https://doi.org/10.1109/wispnet.2016.7566257

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1. Detecting Copy Move Image Forgery using a Deep Learning Model: A Review;2023 International Conference on Artificial Intelligence and Applications (ICAIA) Alliance Technology Conference (ATCON-1);2023-04-21

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