On the benchmarking of ResNet forgery image model using different datasets
Conference paper
Hossain, F. and Dagiuklas, A. (2022). On the benchmarking of ResNet forgery image model using different datasets. Human-Centered Cognitive Systems. Shangai, China 18 Nov - 17 Dec 2022
Authors | Hossain, F. and Dagiuklas, A. |
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Type | Conference paper |
Abstract | This paper presents the benchmarking and improve- ment of the ResNet image forgery model using three different datasets (CASIA, Columbia, and LSBU). The model is based on classification, where forgery images have been edited using cut-paste modification technique.The images are categorized to check if the algorithm can successfully identify the difference between the original and the forgery image. All images have been pre-processed with Gray-Edge detectors to obtain get better classification results. Experimental results have shown that the Gray-edge technique has improved the accuracy across all image datasets. |
Keywords | Image Forgery, ResNet, LSBU-Columbia-CASIA image datasets |
Year | 2022 |
Web address (URL) | http://hccs.gaasnetwork.org/ |
Accepted author manuscript | License File Access Level Open |
Publication dates | |
18 Dec 2022 | |
Publication process dates | |
Accepted | 14 Nov 2022 |
Deposited | 29 Nov 2022 |
Permalink -
https://openresearch.lsbu.ac.uk/item/92q0v
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