A deep neural network with hybrid spotted hyena optimizer and grasshopper optimization algorithm for copy move forgery detection-Reference-Cited by-同舟云学术

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A deep neural network with hybrid spotted hyena optimizer and grasshopper optimization algorithm for copy move forgery detection

Published:2022-11-23 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Gupta Ruchi,Singh Pushpa,Alam Tanweer,Agarwal Shivani

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/s11042-022-14163-6.pdf

Reference41 articles.

1. Abdel-Basset M, Manogaran G, Fakhry AE, El-Henawy I (2020) 2-levels of clustering strategy to detect and locate copy-move forgery in digital images. Multimed Tools Appl 79(7):5419–5437

2. Agarwal R, Verma OP (2020) An efficient copy move forgery detection using deep learning feature extraction and matching algorithm. Multimed Tools Appl 79(11):7355–7376

3. Agarwal R, Verma OP (2021) Robust copy-move forgery detection using modified superpixel based FCM clustering with emperor penguin optimization and block feature matching. Evol Syst 1–15

4. Agarwal R, Verma OP (2020) An efficient copy move forgery detection using deep learning feature extraction and matching algorithm. Multimed Tools Appl 79(11):7355–7376

5. Ahmad M, Khursheed F (2021) A novel image tamper detection approach by blending forensic tools and optimized CNN: Sealion customized firefly algorithm. Multimed Tools Appl 1–25

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2. Fused Deep Representation of Traditional Features for Copy-Move Forgery Detection;2024 International Conference on Machine Intelligence and Smart Innovation (ICMISI);2024-05-12

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4. CCLHF-Net: Constrained Convolution Layer and Hybrid Features-Based Skip Connection Network for Image Forgery Detection;Arabian Journal for Science and Engineering;2024-04-18

5. Image forgery detection in forensic science using optimization based deep learning models;Multimedia Tools and Applications;2023-10-20

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