The block diagram for the proposed methodology.

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Fig. 3. Comparative analysis of proposed RDLNN based on sensitivity,...

Fig. 4. Comparative analysis of proposed RDLNN based on precision,...

Fig. 5. Comparative analysis of proposed RDLNN based on FPR, FNR, and MCC.

RDLNN-based Image Forgery Detection and Forged Region Detection Using MOT

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Full-text available

Nov 2022

Akram Hatem Saber
Mohd Ayyub Khan
Basim Galeb Mejbel

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... dissimilar blocks are evaluated using the MOT algorithm, and the forged region of an image is detected more precisely. Figure 1 presents the block diagram of the proposed technique. ...

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Figure 3: Classifications of feature extraction methods for copy-move...

Figure 4: The architecture of the proposed 10-layer CNN Wu et al. [110]...

Figure 5: The layout, architecture and parameter settings of the CNN...

A Thorough Investigation on Image Forgery Detection

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Image Forgery Detection based on Fusion of Lightweight Deep Learning Models

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Sai Chetan Panathukula
Keshav Kamtam
Gujjar Sai Praharshith

The block diagram for the proposed methodology.

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